iteration,point_id,x,y,cluster,centroid_x,centroid_y,probabilities,variance,weight,id,title,keywords,rating_avg,confidence_avg,author,aff,position,site,github,pdf,openreview,poster
1,0,0.08799766,-0.06060414,0,0.04592027600134834,0.004652675863308072,"[0.9610000020148031, 0.0036101233088717995, 7.72417411803021e-12, 0.03536290162418439, 2.697304441648884e-05]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,00Sx577BT3,The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning,numerical simulations;fluid-dynamics;partial differential equations;operator learning,6.666666666666667,3.6666666666666665,Ruben Ohana;Michael McCabe;Lucas Thibaut Meyer;Rudy Morel;Fruzsina Julia Agocs;Miguel Beneitez;Marsha Berger;Blakesley Burkhart;Stuart B. Dalziel;Drummond Buschman Fielding;Daniel Fortunato;Jared A. Goldberg;Keiya Hirashima;Yan-Fei Jiang;Rich Kerswell;Suryanarayana Maddu;Jonah M. Miller;Payel Mukhopadhyay;Stefan S. Nixon;Jeff Shen;Romain Watteaux;Bruno Régaldo-Saint Blancard;François Rozet;Liam Holden Parker;Miles Cranmer;Shirley Ho,"Flatiron Institute;University of Colorado, Boulder;INRIA;Flatiron Institute;Flatiron Institute;University of Cambridge;Flatiron Institute;Rutgers University;University of Cambridge;Simons Foundation;Flatiron Institute;Flatiron Institute;Simons Foundation;University of Cambridge;Flatiron Institute/Simons Foundation;Los Alamos National Laboratory;University of California, Berkeley;University of Cambridge;Princeton University;CEA;Flatiron Institute;Flatiron Institute;Flatiron Institute;University of Cambridge;Carnegie Mellon University;The University of Tokyo",Postdoc;PhD student;PhD student;Postdoc;Postdoc;Postdoc;Full Professor;Assistant Professor;Director of the GK Batchelor Laboratory;Postdoc;Researcher;Postdoc;Researcher;Full Professor;Postdoc;Researcher;Postdoc;PhD student;PhD student;Researcher;Postdoc;Intern;Researcher;Assistant Professor;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/97882,,,,
1,1,-0.08406016,0.2851326,2,-0.09399681602352898,0.3334173716850977,"[0.0032659950178664447, 9.674464378693313e-17, 0.9942752758117072, 4.324628379884822e-13, 0.002458729169993784]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,00uVk06eVK,On the Noise Robustness of In-Context Learning for Text Generation,In-Context Learning;Large Language Models;Noise Robustness,6.333333333333333,3.0,Hongfu Gao;Feipeng Zhang;Wenyu Jiang;Jun Shu;Feng Zheng;Hongxin Wei,Xi'an Jiaotong University;Xi'an Jiaotong University;Nanjing University;Xi'an Jiaotong University;Southern University of Science and Technology;Southern University of Science and Technology,MS student;Full Professor;PhD student;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96962,,,https://openreview.net/forum?id=00uVk06eVK,/media/PosterPDFs/NeurIPS%202024/96962.png?t=1731587881.4159098
1,2,-0.16364236,-0.11411294,4,-0.21850191112381967,-0.004302541343377307,"[0.32233174048731567, 1.909954497691898e-07, 1.0319537967163742e-10, 0.06317067208854182, 0.6144973963254974]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,01I55gys19,Few-Class Arena: A Benchmark for Efficient Vision Model Selection and Dataset Difficulty,few-class;efficiency;neural network;convolutional neural network;transformer;dataset difficulty measurement;scaling law,5.0,3.3333333333333335,Bryan Bo Cao;Lawrence O'Gorman;Michael Coss;Shubham Jain,Nokia networks GmbH;State University of New York at Stony Brook,Intern;Assistant Professor,,,,,
1,3,0.07371062,-0.27021888,3,-0.1311631712723375,-0.28463581165563745,"[0.10367272859160921, 0.14631356239915883, 9.005220360805688e-24, 0.7500136597245377, 4.928469434669066e-08]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,01XV5Za56k,Testing Calibration in Nearly-Linear Time,Calibration;Property testing;Linear programming,6.25,3.25,Lunjia Hu;Arun Jambulapati;Kevin Tian;Chutong Yang,Stanford University;Stanford University;Stanford University;University of Texas at Austin,PhD student;PhD student;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96961,,,https://openreview.net/forum?id=01XV5Za56k,
1,4,-0.1284643,0.3103237,2,-0.09399681602352898,0.3334173716850977,"[0.0003224283552737136, 1.474986441194567e-19, 0.9986732951649601, 4.632228587330358e-15, 0.001004276479761642]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,01lhHg8H9p,GLBench: A Comprehensive Benchmark for Graph with Large Language Models,Graph learning;Large Language Model;Zero-Shot,6.75,4.0,Yuhan Li;Peisong Wang;Xiao Zhu;Aochuan Chen;Haiyun Jiang;Deng Cai;Victor Wai Kin Chan;Jia Li,"Hong Kong University of Science and Technology;Tsinghua University;Beijing University of Posts and Telecommunications;Hong Kong University of Science and Technology;Tencent AI Lab;Tencent AI Lab;Shenzhen International Graduate School, Tsinghua University;Hong Kong University of Science and Technology",PhD student;MS student;Undergrad student;PhD student;Researcher;Research Scientist;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97881,,,,/media/PosterPDFs/NeurIPS%202024/97881.png?t=1731478194.2539835
1,5,-0.23808402,0.26056772,2,-0.09399681602352898,0.3334173716850977,"[8.552755778850757e-05, 1.636993024538528e-21, 0.9906472779799465, 2.176526971298093e-14, 0.0092671944622432]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,01qa1ZJs65,Bridge the Modality and Capability Gaps in Vision-Language Model Selection,Vision-Language Model;Model Selection;Zero-Shot Image Classification,5.25,4.0,Chao Yi;Yuhang He;De-Chuan Zhan;Han-Jia Ye,Nanjing University;Nanjing University;Nanjing University;Nanjing University,MS student;Undergrad student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96960,,,https://openreview.net/forum?id=01qa1ZJs65,/media/PosterPDFs/NeurIPS%202024/96960.png?t=1731123927.9174762
1,6,-0.10493148,-0.30384988,3,-0.1311631712723375,-0.28463581165563745,"[0.047221013204990066, 0.0002848157624912368, 6.525928147428476e-23, 0.9524209402134818, 7.323081903706098e-05]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,01s5ODIHKd,FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space,deep watermarking;latent frequency optimization,5.5,3.75,YiYang Guo;Ruizhe Li;Mude Hui;Hanzhong Allan Guo;Chen Zhang;Chuangjian Cai;Le Wan;Shangfei Wang,"University of Science and Technology of China;University of California, Santa Cruz;Renmin University of China;Tsinghua University;University of Science and Technology of China;University of Science and Technology of China",MS student;PhD student;MS student;PhD student;Full Professor;PhD student,https://neurips.cc/virtual/2024/poster/96959,,,https://openreview.net/forum?id=01s5ODIHKd,/media/PosterPDFs/NeurIPS%202024/96959.png?t=1730176108.8718698
1,7,-0.295713,-0.42771262,3,-0.1311631712723375,-0.28463581165563745,"[0.005259129124738324, 1.4069793709380055e-06, 5.700181925132596e-28, 0.9947261888465835, 1.3275049307222582e-05]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,02CIZ8qeDc,PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection,3D anomaly detection;Zero-shot 3D anomaly detection,6.0,3.6666666666666665,Qihang Zhou;Jiangtao Yan;Shibo He;Wenchao Meng;Jiming Chen,Zhejiang University;Zhejiang University;Zhejiang University;Zhejiang University,PhD student;MS student;Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96958,,,https://openreview.net/forum?id=02CIZ8qeDc,/media/PosterPDFs/NeurIPS%202024/96958.png?t=1731476864.9817398
1,8,-0.3188932,-0.023905918,4,-0.21850191112381967,-0.004302541343377307,"[0.00472881192788093, 2.5980413326266375e-14, 6.239642665604645e-06, 2.0895699138269544e-05, 0.9952440527302892]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,02HWT9c4Lp,Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion,Semantic Scene completion，Voxel Proposal，Knowledge Distillation,5.5,4.0,Lubo Wang;Di Lin;Kairui Yang;Ruonan Liu;Qing Guo;Wuyuan Xie;Miaohui Wang;Lingyu Liang;Yi Wang;Ping Li,"Tianjin University;Tianjin University;Tianjin University;Tianjin University; Agency for Science, Technology and Research (A*STAR));Department of Software Engineering, Shenzhen University;Shenzhen University;South China University of Technology;Shenzhen University;The Hong Kong Polytechnic University",MS student;Associate Professor;PhD student;Associate Professor;Researcher;Associate Professor;Associate Professor;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96957,,,https://openreview.net/forum?id=02HWT9c4Lp,/media/PosterPDFs/NeurIPS%202024/96957.png?t=1731159292.6143699
1,9,0.52375084,0.03593809,1,0.40261197255458847,-0.08318364083571851,"[0.00010751321889685142, 0.9998920594071498, 5.572186481549969e-17, 4.2737395327678336e-07, 2.3328507267174085e-26]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,02r24A8doi,Achieving Constant Regret in Linear Markov Decision Processes,Reinforcement learning;Constant regret;Misspecified linear MDP,5.25,2.75,Weitong Zhang;Zhiyuan Fan;Jiafan He;Quanquan Gu,"Massachusetts Institute of Technology;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles",PhD student;PhD student;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96956,,,https://openreview.net/forum?id=02r24A8doi,
1,10,-0.24769914,0.06194072,4,-0.21850191112381967,-0.004302541343377307,"[0.006236343880692106, 1.2033773478392555e-14, 0.0006284588481700384, 4.4039671729755225e-07, 0.9931347568744087]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,04EC4ZnZJj,MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers,transformer architecture;large language model;computational complexity reduction,6.0,3.5,Ning Ding;Yehui Tang;Haochen Qin;Zhenli Zhou;Chao Xu;Lin Li;Kai Han;Liao Heng;Yunhe Wang,"Peking University;Huawei Technologies Ltd.;Huawei Technologies Ltd.;Peking University;Peking University;Huawei Noah's Ark Lab;, Tsinghua University;Huawei Noah's Ark Lab",PhD student;Researcher;Researcher;MS student;Full Professor;Principal Researcher;Principal Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96955,,,https://openreview.net/forum?id=04EC4ZnZJj,
1,11,0.45866024,0.07679337,1,0.40261197255458847,-0.08318364083571851,"[0.004789577074593344, 0.9952075616560121, 6.050415165331628e-13, 2.8612687894952684e-06, 3.120589578683671e-21]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,06JRFVK88O,Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games,Multi-agent Reinforcement Learning;Imitation Learning,6.666666666666667,3.0,The Viet Bui;Tien Anh Mai;Thanh Hong Nguyen,Singapore Management University;University of Oregon;Singapore Management University,Assistant Professor;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96954,,,https://openreview.net/forum?id=06JRFVK88O,/media/PosterPDFs/NeurIPS%202024/96954.png?t=1731744891.8886228
1,12,-0.21952832,-0.2596673,3,-0.1311631712723375,-0.28463581165563745,"[0.07127129555808932, 1.2633519665545733e-06, 6.724970057911959e-18, 0.9111330421871165, 0.017594398902827598]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,06Vt6f2js7,SyncTweedies: A General Generative Framework Based on Synchronized Diffusions,Diffusion Models;Synchronization;Texturing;3D Gaussian Splatting;Mesh;Panorama,6.666666666666667,3.6666666666666665,Jaihoon Kim;Juil Koo;Kyeongmin Yeo;Minhyuk Sung,KAIST;Adobe Systems;Korea Advanced Institute of Science & Technology;Korea Advanced Institute of Science & Technology,MS student;Intern;Undergrad student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96953,,,https://openreview.net/forum?id=06Vt6f2js7,
1,13,0.5387558,-0.021885695,1,0.40261197255458847,-0.08318364083571851,"[1.4774489013496798e-05, 0.9999847920885987, 1.1845671195984715e-20, 4.334223877752761e-07, 2.4962729196524225e-28]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,07N0qoaZ2L,Improved Analysis for Bandit Learning in Matching Markets,Bandits;Matching markets;Stable matching;Stable regret;Exploration and exploitation;$\alpha$-condition,5.5,3.0,Fang Kong;Zilong Wang;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;John Hopcroft Center, Shanghai Jiao Tong University",PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96952,,,https://openreview.net/forum?id=07N0qoaZ2L,/media/PosterPDFs/NeurIPS%202024/96952.png?t=1731746661.9360106
1,14,-0.31746334,-0.03755091,4,-0.21850191112381967,-0.004302541343377307,"[0.005726122721549833, 6.926503508842367e-14, 2.0724985147437775e-06, 4.743053884860861e-05, 0.9942243742410175]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,08A6X7FSTs,Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text,Text-to-3D Scene Generation;Latent Diffusion Models,5.5,4.5,Xinyang Li;Zhangyu Lai;Linning Xu;Yansong Qu;Liujuan Cao;Shengchuan Zhang;Bo Dai;Rongrong Ji,Xiamen University;Xiamen University;Xiamen University;Xiamen University;Xiamen University;Shanghai AI Laboratory;Xiamen University;The Chinese University of Hong Kong,PhD student;MS student;PhD student;Full Professor;Assistant Professor;Scientist;Full Professor;Ph.D. student,https://neurips.cc/virtual/2024/poster/96951,,,https://openreview.net/forum?id=08A6X7FSTs,/media/PosterPDFs/NeurIPS%202024/96951.png?t=1732593534.8700738
1,15,0.21572201,0.15297481,0,0.04592027600134834,0.004652675863308072,"[0.9997382412285086, 0.00022492052092407046, 3.254079281824419e-05, 4.281899492774582e-06, 1.555825628727213e-08]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,08GbdALmEs,Learning Versatile Skills with Curriculum Masking,reinforcement learning;unsupervised pretraining;masked prediction;curriculum learning,5.25,3.25,Yao Tang;Zhihui Xie;Zichuan Lin;Deheng Ye;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;Tencent AI Lab;Tencent;John Hopcroft Center, Shanghai Jiao Tong University",Undergrad student;MS student;Researcher;Principal Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96950,,,https://openreview.net/forum?id=08GbdALmEs,/media/PosterPDFs/NeurIPS%202024/96950.png?t=1733319308.3295946
1,16,-0.17784788,-0.16018736,4,-0.21850191112381967,-0.004302541343377307,"[0.33351309216588193, 7.210986196262135e-07, 1.1015125835204239e-12, 0.29616321114666644, 0.3703229755877306]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,08nbMTxazb,Chicks4FreeID: A Benchmark Dataset for Chicken Re-Identification,animal re-identification;chicken re-identification;chicken dataset;re-identification dataset;benchmark dataset;closed-set re-identification;computer vision;chicken instance segmentation;poultry;livestock,4.75,4.0,Daria Kern;Tobias Schiele;Ulrich Klauck;Winfred Ingabire,Glasgow Caledonian University;Hochschule Aalen;Glasgow Caledonian University,PhD student;Full Professor;Lecturer,,,,,
1,17,0.12485067,-0.17534988,3,-0.1311631712723375,-0.28463581165563745,"[0.35969524678899134, 0.24945115311311714, 1.336528123427154e-18, 0.3908535182000549, 8.189783658746366e-08]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,08oUnmtj8Q,FSEO: A Few-Shot Evolutionary Optimization Framework for Expensive Multi-Objective Optimization and Constrained Optimization,Expensive optimization;few-shot optimization;multi-objective optimization;constrained optimization;surrogate-assisted evolutionary optimization,4.5,3.5,Xunzhao Yu,,,,,,,
1,18,-0.045080878,-0.32160506,3,-0.1311631712723375,-0.28463581165563745,"[0.04562771302136759, 0.003851214224858593, 3.587565445717475e-25, 0.950518240880963, 2.831872810621381e-06]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,09RKw0vXjR,Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations,feature selection;sparse coding;dictionary learning;compressed sensing;iterative hard thresholding;pruning method,5.75,3.0,Yasutoshi Ida;Sekitoshi Kanai;Atsutoshi Kumagai;Tomoharu Iwata;Yasuhiro Fujiwara,NTT;NTT;NTT;NTT;NTT,Researcher;Researcher;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96949,,,https://openreview.net/forum?id=09RKw0vXjR,/media/PosterPDFs/NeurIPS%202024/96949.png?t=1733375377.8112724
1,19,-0.29219365,-0.1354431,4,-0.21850191112381967,-0.004302541343377307,"[0.03988952455276641, 1.941668455013209e-10, 2.7439085130769777e-10, 0.01701592832211219, 0.9430945466565637]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,09nyBqSdUz,RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance,Consistent image generation;Diverse image generation;Improve temporal-consistency;Feature injection from multiple images,5.5,4.0,Jiaojiao Fan;Haotian Xue;Qinsheng Zhang;Yongxin Chen,Georgia Institute of Technology;Georgia Institute of Technology;Georgia Institute of Technology;NVIDIA,PhD student;PhD student;Associate Professor;Research Intern,https://neurips.cc/virtual/2024/poster/96948,,,https://openreview.net/forum?id=09nyBqSdUz,/media/PosterPDFs/NeurIPS%202024/96948.png?t=1731392354.7708242
1,20,0.22983314,0.005944166,0,0.04592027600134834,0.004652675863308072,"[0.8726510071091341, 0.1236175974226023, 6.397277890466351e-11, 0.0037313936783736337, 1.725917295764124e-09]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0AumdfLzpK,A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations,Visual Reinforcement Learning;Generalization,6.0,4.0,Wonil Song;Hyesong Choi;Kwanghoon Sohn;Dongbo Min,Yonsei Univ.;Ewha Womans University;Yonsei University;Ewha Womans University,PhD student;PhD student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96947,,,https://openreview.net/forum?id=0AumdfLzpK,/media/PosterPDFs/NeurIPS%202024/96947.png?t=1732451612.1247888
1,21,-0.2313607,0.15489271,4,-0.21850191112381967,-0.004302541343377307,"[0.005415360369404412, 1.1773901720972085e-16, 0.18869304900753484, 1.8474717090081445e-09, 0.8058915887755889]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0AwMciNShl,"Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality",Human evaluation;text-to-video models,5.25,4.0,Tianle Zhang;Langtian Ma;Yuchen Yan;Yuchen Zhang;Yue Yang;Ziyao Guo;Wenqi Shao;Kai Wang;Yang You;Yu Qiao;Ping Luo;Kaipeng Zhang,University of Electronic Science and Technology of China;Southern University of Science and Technology;The University of Nottingham Ningbo China;University of Electronic Science and Technology of China;Xidian University;Shanghai AI Laboratory;National University of Singapore;National University of Singapore;Shanghai AI Laboratory;The University of Hong Kong;Shanghai Jiaotong University,Undergrad student;Undergrad student;Undergrad student;Undergrad student;MS student;Researcher;PhD student;Professor;Researcher;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96946,,,https://openreview.net/forum?id=0AwMciNShl,/media/PosterPDFs/NeurIPS%202024/96946.png?t=1729079669.652648
1,22,0.44196302,-0.22339565,1,0.40261197255458847,-0.08318364083571851,"[9.252365565376698e-06, 0.9999716321016106, 1.0635862808138545e-30, 1.9115532824036688e-05, 1.825476793420965e-25]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0C3bLHwjsY,Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions,Online Matching;Competitive Analysis;Fairness Maximization,6.25,3.0,Will Ma;Pan Xu,Columbia University;New Jersey Institute of Technology,Assistant Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96945,,,https://openreview.net/forum?id=0C3bLHwjsY,/media/PosterPDFs/NeurIPS%202024/96945.png?t=1731641014.5806563
1,23,0.31953293,-0.23248373,1,0.40261197255458847,-0.08318364083571851,"[0.00039576522117051703, 0.9985528973984195, 7.338681148388485e-28, 0.0010513373804100139, 1.9664526729881777e-18]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0DE1dLMW2b,Quantum algorithm for large-scale market equilibrium computation,market equilibrium computation;quantum algorithm,6.0,2.75,Po-Wei Huang;Patrick Rebentrost,Centre for Quantum Technologies;National University of Singapore,Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96944,,,https://openreview.net/forum?id=0DE1dLMW2b,/media/PosterPDFs/NeurIPS%202024/96944.png?t=1731426989.5298698
1,24,0.0025802255,-0.08199731,0,0.04592027600134834,0.004652675863308072,"[0.9318091882181055, 0.00020624808115773466, 1.5882418822627e-11, 0.06517485557460803, 0.002809708110246239]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0EfUYVMrLv,Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment,non-stationary environments;continuous distribution shift;test-time adaptation;unlabeled data,6.666666666666667,4.0,Zhen-Yu Zhang;Zhiyu Xie;Huaxiu Yao;Masashi Sugiyama,"RIKEN;Stanford University;Department of Computer Science, University of North Carolina at Chapel Hill;The University of Tokyo",Postdoc;MS student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96943,,,https://openreview.net/forum?id=0EfUYVMrLv,/media/PosterPDFs/NeurIPS%202024/96943.png?t=1731687693.6296034
1,25,0.023439856,-0.079839304,0,0.04592027600134834,0.004652675863308072,"[0.9365120974650514, 0.0004649476329699633, 9.43660473748381e-12, 0.0620863849783889, 0.0009365699141530529]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0G0VpMjKyV,Sketching for Distributed Deep Learning: A Sharper Analysis,sketching;distributed learning;federated learning;optimization,5.666666666666667,4.0,Mayank Shrivastava;Berivan Isik;Qiaobo Li;Sanmi Koyejo;Arindam Banerjee,"University of Illinois, Urbana Champaign;Stanford University;Department of Computer Science, University of Illinois at Urbana-Champaign;University of Illinois, Urbana Champaign;Google",MS student;PhD student;PhD student;Professor;Research Scientist,https://neurips.cc/virtual/2024/poster/96942,,,https://openreview.net/forum?id=0G0VpMjKyV,/media/PosterPDFs/NeurIPS%202024/96942.png?t=1733481266.9121125
1,26,-0.06371302,0.3954228,2,-0.09399681602352898,0.3334173716850977,"[0.00012402458843111796, 9.809417459177354e-21, 0.9998672617000046, 3.707108009713051e-18, 8.713711564161742e-06]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,0G5OK5vmmg,WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts,Benchmark;Large Language Models;Classical Chinese Literature and Language Arts,6.25,2.75,Jiahuan Cao;Yang Liu;Yongxin Shi;Kai Ding;Lianwen Jin,South China University of Technology;South China University of Technology;South China University of Technology;INTSIG Information;South China University of Technology,MS student;MS student;PhD student;Researcher;Professor,https://neurips.cc/virtual/2024/poster/97880,,,,/media/PosterPDFs/NeurIPS%202024/97880.png?t=1730896668.2191207
1,27,-0.2963673,0.015343715,4,-0.21850191112381967,-0.004302541343377307,"[0.004025573496148959, 8.30215531739575e-15, 6.349280583428496e-05, 2.786206062738948e-06, 0.9959081474919457]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0G8AXwtmy2,T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition,harmful dataset;harmful content detection;Vision Language Model,6.5,3.75,Chen Yeh;You-Ming Chang;Wei-Chen Chiu;Ning Yu,National Yang Ming Chiao Tung University;National Yang Ming Chiao Tung University;National Chiao Tung University,MS student;MS student;Associate Professor,https://neurips.cc/virtual/2024/poster/97879,,,,/media/PosterPDFs/NeurIPS%202024/97879.png?t=1730218737.4487233
1,28,0.08612508,0.3898904,2,-0.09399681602352898,0.3334173716850977,"[0.005582459458721729, 4.764073000161274e-15, 0.9944173949857597, 1.160172678290867e-15, 1.4555551276842973e-07]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,0Gl5WxY6es,Grounding Multimodal Large Language Models in Actions,Embodied AI;Multimodal Large Language Models;Reinforcement Learning;Imitation Learning,6.0,3.6666666666666665,Andrew Szot;Bogdan Mazoure;Harsh Agrawal;R Devon Hjelm;Zsolt Kira;Alexander T Toshev,Georgia Institute of Technology;Apple;Apple;Apple;Georgia Institute of Technology;Apple,PhD student;Research Scientist;Researcher;Researcher;Assistant Professor;research scientist,https://neurips.cc/virtual/2024/poster/96941,,,https://openreview.net/forum?id=0Gl5WxY6es,
1,29,-0.20296153,0.2345368,2,-0.09399681602352898,0.3334173716850977,"[0.0008568330877808954, 6.741648899891591e-19, 0.9491985707660823, 1.7748491800779232e-12, 0.04994459614436192]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,0Gmi8TkUC7,GenAI Arena: An Open Evaluation Platform for Generative Models,Evaluation;Benchmark;Platform;Generative Model,6.0,3.5,Dongfu Jiang;Max Ku;Tianle Li;Yuansheng Ni;Shizhuo Sun;Rongqi Fan;Wenhu Chen,Allen Institute for Artificial Intelligence;University of Waterloo;University of Waterloo;University of Toronto;NVIDIA;University of Waterloo,Intern;MS student;MS student;Undergrad student;Intern;Assistant Professor,https://neurips.cc/virtual/2024/poster/97878,,,,/media/PosterPDFs/NeurIPS%202024/97878.png?t=1730329031.3167162
1,30,-0.3021013,-0.23802479,3,-0.1311631712723375,-0.28463581165563745,"[0.078216314327577, 2.084693702197382e-08, 5.116143815581607e-15, 0.7496380649648993, 0.1721455998605815]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,0HRRNEAQFp,A General Protocol to Probe Large Vision Models for 3D Physical Understanding,3D physical scene understanding; Representation probing protocol; Benchmark and evaluation,6.333333333333333,4.0,Guanqi Zhan;Chuanxia Zheng;Weidi Xie;Andrew Zisserman,University of Oxford;University of Oxford;Shanghai Jiaotong University,PhD student;Postdoc;Associate Professor,https://neurips.cc/virtual/2024/poster/96940,,,https://openreview.net/forum?id=0HRRNEAQFp,/media/PosterPDFs/NeurIPS%202024/96940.png?t=1731705235.0575316
1,31,0.40233114,0.06031101,1,0.40261197255458847,-0.08318364083571851,"[0.029252290954653103, 0.9707209776424296, 3.2371448930461047e-12, 2.6731399680118383e-05, 8.104664747159253e-18]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0JSKjdePGq,When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL,reinforcement learning;continuous-time,6.75,3.25,Lenart Treven;Bhavya Sukhija;Yarden As;Florian Dorfler;Andreas Krause,"Swiss Federal Institute of Technology;ETHZ - ETH Zurich;Department of Computer Science, ETHZ - ETH Zurich;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96939,,,https://openreview.net/forum?id=0JSKjdePGq,/media/PosterPDFs/NeurIPS%202024/96939.png?t=1730197260.75527
1,32,-0.31179968,-0.050893012,4,-0.21850191112381967,-0.004302541343377307,"[0.007341226682350194, 2.3370368689936066e-13, 6.089962962811924e-07, 0.00011082469992327721, 0.9925473396211966]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0KseSacluJ,CoFie: Learning Compact Neural Surface Representations with Coordinate Fields,Neural Surface Representation;Shape Auto-Decoding;Coordinate Field.,5.0,4.0,Hanwen Jiang;Haitao Yang;Georgios Pavlakos;Qixing Huang,University of Texas at Austin;The University of Texas at Austin;University of Texas at Austin;University of Texas at Austin,PhD student;PhD student;Assistant Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96938,,,https://openreview.net/forum?id=0KseSacluJ,
1,33,0.11298243,0.035079706,0,0.04592027600134834,0.004652675863308072,"[0.9988378758654758, 0.00027571342096332737, 4.173473036602718e-08, 0.000868366435480037, 1.8002543350531202e-05]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0KvYLaTBTE,Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference,Generative models;Reinforcement learning;Decision transformer,6.333333333333333,3.0,Deqian Kong;Dehong Xu;Minglu Zhao;Bo Pang;Jianwen Xie;Andrew Lizarraga;Yuhao Huang;Sirui Xie;Ying Nian Wu,"University of California, Los Angeles;Amazon;University of California, Los Angeles;University of California, Los Angeles;Xi'an Jiaotong University;University of California, Los Angeles;University of California, Los Angeles;UCLA",PhD student;Intern;PhD student;PhD student;PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96937,,,https://openreview.net/forum?id=0KvYLaTBTE,
1,34,-0.23456638,0.06657637,4,-0.21850191112381967,-0.004302541343377307,"[0.007942055272435529, 2.337500706355445e-14, 0.0006989851658039866, 4.56362283567183e-07, 0.9913585031994534]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0LXotew9Du,KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization,Quantization;KV Cache;LLM Inference;Compression;Long Context Length,6.25,3.25,Coleman Richard Charles Hooper;Sehoon Kim;Hiva Mohammadzadeh;Michael W. Mahoney;Sophia Shao;Kurt Keutzer;Amir Gholami,"University of California, Berkeley;University of California, Berkeley;University of California, Berkeley;University of California, Berkeley",PhD student;PhD student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96936,,,https://openreview.net/forum?id=0LXotew9Du,
1,35,0.11017645,-0.16371755,0,0.04592027600134834,0.004652675863308072,"[0.4741398117776026, 0.13388913934504604, 1.284059610475572e-17, 0.39197065652422397, 3.9235312746065776e-07]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0Lb8vZT1DB,Reliable Learning of Halfspaces under Gaussian Marginals,reliable learning;agnostic learning;halfspace;proper leaning;statistical query,7.25,2.25,Ilias Diakonikolas;Lisheng Ren;Nikos Zarifis,"University of Wisconsin - Madison;University of Wisconsin - Madison;University of Wisconsin, Madison",Full Professor;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96935,,,https://openreview.net/forum?id=0Lb8vZT1DB,
1,36,0.1429859,0.059452157,0,0.04592027600134834,0.004652675863308072,"[0.9992775371382331, 0.000397186511474393, 1.4339323089959214e-07, 0.00032240409466069084, 2.7288624008410396e-06]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0LfgE6kvKZ,Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning,Federated Learning; Model Merging,5.0,3.6666666666666665,Minghui Chen;Meirui Jiang;Xin Zhang;Qi Dou;Zehua Wang;Xiaoxiao Li,"University of British Columbia;Meta Facebook;The Chinese University of Hong Kong;University of British Columbia;University of British Columbia;Department of Computer Science and Engineering, The Chinese University of Hong Kong",PhD student;Research Scientist;Assistant Professor;Researcher;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96934,,,https://openreview.net/forum?id=0LfgE6kvKZ,/media/PosterPDFs/NeurIPS%202024/96934.png?t=1731518093.5294044
1,37,-0.040502112,0.02318828,0,0.04592027600134834,0.004652675863308072,"[0.9000372974437778, 3.439915724508072e-07, 2.084966519170096e-06, 0.0008261911160259755, 0.09913408248210462]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0Lr9HQijA1,Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations,Imprecise Label Learning,5.75,3.0,Hao Chen;Ankit Shah;Jindong Wang;Ran Tao;Yidong Wang;Xiang Li;Xing Xie;Masashi Sugiyama;Rita Singh;Bhiksha Raj,"Carnegie Mellon University;Accenture;Microsoft Research;Peking University;Microsoft Research Asia;The University of Tokyo;School of Computer Science, Carnegie Mellon University;Mohamed bin Zayed University of Artificial Intelligence",PhD student;Principal Researcher;Researcher;PhD student;Senior Principal Researcher;Full Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96933,,,https://openreview.net/forum?id=0Lr9HQijA1,/media/PosterPDFs/NeurIPS%202024/96933.png?t=1731704880.9846606
1,38,-0.06471333,0.08954511,0,0.04592027600134834,0.004652675863308072,"[0.6500725262364759, 3.166110685424269e-09, 0.0008267806747929298, 2.0590635403637598e-05, 0.34908009928721684]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0MXzbAv8xy,GFT: Graph Foundation Model with Transferable Tree Vocabulary,Graph Foundation Model;Transferability;Computation Tree;Graph Neural Network,6.0,3.75,Zehong Wang;Zheyuan Zhang;Nitesh V Chawla;Chuxu Zhang;Yanfang Ye,University of Notre Dame;University of Notre Dame;University of Notre Dame;University of Notre Dame,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96932,,,https://openreview.net/forum?id=0MXzbAv8xy,
1,39,0.06407858,0.09707585,0,0.04592027600134834,0.004652675863308072,"[0.9992848146726905, 1.8826410546362493e-06, 3.6326326982560525e-05, 3.7108356063240894e-05, 0.0006398680032090677]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0NMzBwqaAJ,Not All Tokens Are What You Need for Pretraining,pre-training;next token prediction;data optimization;data selection,7.666666666666667,4.0,Zhenghao Lin;Zhibin Gou;Yeyun Gong;Xiao Liu;yelong shen;Ruochen Xu;Chen Lin;Yujiu Yang;Jian Jiao;Nan Duan;Weizhu Chen,Xiamen University;Microsoft;Microsoft Research Asia;Microsoft Research;Xiamen University;Tsinghua University;Microsoft;Microsoft Research Asia;Microsoft GenAI,MS student;Intern;Researcher;Researcher;Full Professor;Full Professor;Principal Researcher;Principal Researcher;Vice President,https://neurips.cc/virtual/2024/poster/96931,,,https://openreview.net/forum?id=0NMzBwqaAJ,/media/PosterPDFs/NeurIPS%202024/96931.png?t=1733724962.7310221
1,40,-0.021407472,0.09407413,0,0.04592027600134834,0.004652675863308072,"[0.9324394139594736, 3.1156156027442466e-08, 0.00040286415203111915, 2.7864405126243902e-05, 0.06712982632721294]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0NQzQVu9tY,DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors,representation learning;offline reinforcement learning;behavioral cloning;visual distractor,7.0,3.0,Joseph Ortiz;Antoine Dedieu;Wolfgang Lehrach;J Swaroop Guntupalli;Carter Wendelken;Ahmad Humayun;Sivaramakrishnan Swaminathan;Guangyao Zhou;Miguel Lazaro-Gredilla;Kevin Patrick Murphy,Google DeepMind;Google DeepMind;Google Deepmind;Google DeepMind;Google;Google DeepMind;Google DeepMind;Google DeepMind;Google Deepmind;Google,Researcher;Researcher;Researcher;Researcher;Researcher;Researcher;Research Engineer;Research Scientist;Research Scientist;Principal Researcher,https://neurips.cc/virtual/2024/poster/97877,,,,/media/PosterPDFs/NeurIPS%202024/97877.png?t=1733266397.4133346
1,41,-0.056248758,0.025906589,0,0.04592027600134834,0.004652675863308072,"[0.8095415164619693, 1.2951827118975427e-07, 4.119305035234441e-06, 0.0006260870059660554, 0.18982814770875808]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0SMhqvgHST,EEVEE and GATE: Finding the right benchmarks and how to run them seamlessly,multi-modal;benchmarks;machine learning;model evaluation;benchmark frameworks,6.0,4.0,Antreas Antoniou;Eleni Triantafillou;Hugo Larochelle;Sebastien Montella;Fady Rezk;Kiyoon Kim;Linus Ericsson;Pavlos Vougiouklis;Justin Engelmann;Elliot J. Crowley;Srihari Humbarwadi;Yi Liu;Guang Yang;Jeff Z. Pan;Amos Storkey,"Google;Google;Huawei Technologies Ltd.;Samsung;Deargen;University of Edinburgh, University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh, University of Edinburgh;University of Edinburgh",Researcher;Research Scientist;Researcher;Intern;Researcher;Postdoc;Researcher;Assistant Professor;Researcher;Full Professor;Full Professor,,,,,
1,42,-0.15132618,0.02146309,4,-0.21850191112381967,-0.004302541343377307,"[0.09832097703664125, 2.0034667043509203e-10, 1.025127196184222e-05, 7.201636967516488e-05, 0.9015967551213753]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0SRJBtTNhX,IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors,Graph Machine Learning;Graph Data Augmentation;Graph Neural Networks,5.5,4.0,Shenghe Zheng;Hongzhi Wang;Xianglong Liu,Harbin Institute of Technology;Harbin Institute of Technology;Harbin Institute of Technology,MS student;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96930,,,https://openreview.net/forum?id=0SRJBtTNhX,/media/PosterPDFs/NeurIPS%202024/96930.png?t=1732617637.3891017
1,43,-0.18518934,0.0027779788,4,-0.21850191112381967,-0.004302541343377307,"[0.04484994091027801, 4.448415250753522e-11, 3.2481227170592724e-06, 7.318670960373645e-05, 0.9550736242129171]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0T8xRFrScB,Benchmarking Counterfactual Image Generation,benchmark;causal inference;counterfactual image generation,7.25,3.75,Thomas Melistas;Nikos Spyrou;Nefeli Gkouti;Pedro Sanchez;Athanasios Vlontzos;Yannis Panagakis;Giorgos Papanastasiou;Sotirios A. Tsaftaris,"University of Athens;University of Athens;University of Athens;University of Edinburgh, University of Edinburgh;Spotify;Pfizer;University of Edinburgh",PhD student;PhD student;PhD student;PhD student;Researcher;Principal Researcher;Professor in machine learning and computer vision,https://neurips.cc/virtual/2024/poster/97876,,,,/media/PosterPDFs/NeurIPS%202024/97876.png?t=1731712408.6398222
1,44,0.5118622,-0.024860546,1,0.40261197255458847,-0.08318364083571851,"[3.74033568319175e-05, 0.9999614892812593, 4.268855222649279e-20, 1.1073619088770351e-06, 1.6279031192725568e-26]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0TUMAAb3of,Queueing Matching Bandits with Preference Feedback,Bandits;Queue;Preference Feedback,6.0,2.5,Jung-hun Kim;Min-hwan Oh,Seoul National University;Seoul National University,Assistant Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96929,,,https://openreview.net/forum?id=0TUMAAb3of,/media/PosterPDFs/NeurIPS%202024/96929.png?t=1733803835.532587
1,45,-0.0018669573,0.3644946,2,-0.09399681602352898,0.3334173716850977,"[0.0014808877216321938, 3.569608427880069e-17, 0.9985099546906303, 9.78862706585379e-16, 9.157587736539737e-06]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,0VeSCjRDBy,Adversarial Moment-Matching Distillation of Large Language Models,Knowledge distillation;Large language models;Imitation learning;Moment-matching;Adversarial training,6.25,3.0,Chen Jia,,,https://neurips.cc/virtual/2024/poster/96928,,,https://openreview.net/forum?id=0VeSCjRDBy,/media/PosterPDFs/NeurIPS%202024/96928.png?t=1731660620.7591212
1,46,-0.24925767,0.015651966,4,-0.21850191112381967,-0.004302541343377307,"[0.008751271452824219, 1.904108777336706e-13, 2.239112894203609e-05, 6.651020044086569e-06, 0.9912196863979992]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0WCFI2Qx85,ScaleKD: Strong Vision Transformers Could Be Excellent Teachers,knowledge distillation;model compression;training acceleration;vision transformer;convolutional neural network;multi-layer perception,6.25,4.5,Jiawei Fan;Chao Li;Xiaolong Liu;Anbang Yao,Intel Labs China;Intel;Intel,Research Intern;Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96927,,,https://openreview.net/forum?id=0WCFI2Qx85,/media/PosterPDFs/NeurIPS%202024/96927.png?t=1731695837.2500114
1,47,0.2804453,-0.1894261,1,0.40261197255458847,-0.08318364083571851,"[0.0035614229504687296, 0.9916380034659878, 8.837466110939935e-24, 0.0048005735835411805, 2.2093692435076132e-15]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0XKvW4ijxp,Learning-Augmented Algorithms with Explicit Predictors,online algorithms;learning-augmented algorithms;scheduling;caching,6.0,4.0,Marek Elias;Haim Kaplan;Yishay Mansour;Shay Moran,"Bocconi University;Technion, Technion;School of Computer Science, Tel Aviv University",Assistant Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96926,,,https://openreview.net/forum?id=0XKvW4ijxp,/media/PosterPDFs/NeurIPS%202024/96926.png?t=1733319671.0065775
1,48,0.37225774,-0.11562894,1,0.40261197255458847,-0.08318364083571851,"[0.0007498254771960463, 0.9990431435887542, 1.1307501151102556e-21, 0.00020703093404972542, 3.7721394901521905e-19]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0XeNkkENuI,The Road Less Scheduled,Stochastic Optimization;Optimization;Convex Optimization;Learning Rates;Learning Rate Schedules,7.5,3.5,Aaron Defazio;Xingyu Alice Yang;Ahmed Khaled;Konstantin Mishchenko;Harsh Mehta;Ashok Cutkosky,Meta;Meta;Princeton University;Samsung;Google Research;Boston University,Research Scientist;Research Engineer;PhD student;Researcher;Software Engineer;Assistant Professor,https://neurips.cc/virtual/2024/poster/96925,,,https://openreview.net/forum?id=0XeNkkENuI,/media/PosterPDFs/NeurIPS%202024/96925.png?t=1730837481.9895687
1,49,0.1460578,0.21914145,0,0.04592027600134834,0.004652675863308072,"[0.9831076641151729, 3.1113500138644485e-07, 0.016889197809427447, 5.898366652629734e-08, 2.7679567319159686e-06]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0ZZMUjZJYF,Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study,LLMs;Learning by Teaching;Reasoning;Mathematical Reasoning;Code Synthesis;Weak-to-Strong Generalization;In-Context Learning;Prompting;Knowledge Distillation;Education-Inspired,6.5,4.0,Xuefei Ning;Zifu Wang;Shiyao Li;Zinan Lin;Peiran Yao;Tianyu Fu;Matthew B. Blaschko;Guohao Dai;Huazhong Yang;Yu Wang,Tsinghua University;KU Leuven;Tsinghua University;Microsoft;Infinigence;Shanghai Jiaotong University;Tsinghua University;Tsinghua University;KU Leuven,Research Assistant Professor;PhD student;PhD student;Senior Researcher;Researcher;Associate Professor;Full Professor;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96924,,,https://openreview.net/forum?id=0ZZMUjZJYF,/media/PosterPDFs/NeurIPS%202024/96924.png?t=1732367562.4969194
1,50,0.07159563,-0.024327766,0,0.04592027600134834,0.004652675863308072,"[0.9902543400816733, 0.0004659921792890681, 5.726409412905504e-10, 0.009145151467489756, 0.00013451569890691372]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0ZeONp33f0,Graph Neural Networks and Arithmetic Circuits,Machine Learning;Graph Neural Networks;Arithmetic Circuits;Computational Complexity,6.5,3.25,Timon Barlag;Vivian Holzapfel;Laura Strieker;Jonni Virtema;Heribert Vollmer,Universität Hannover;Leibniz Universität Hannover;Leibniz Universität Hannover;University of Sheffield;Leibniz Universität Hannover,PhD student;Undergrad student;PhD student;Lecturer;Full Professor,https://neurips.cc/virtual/2024/poster/96923,,,https://openreview.net/forum?id=0ZeONp33f0,/media/PosterPDFs/NeurIPS%202024/96923.png?t=1732106485.9402945
1,51,-0.078428976,-0.18954016,3,-0.1311631712723375,-0.28463581165563745,"[0.35058214083966494, 0.00014133904803836035, 5.765959086196806e-16, 0.6440398252037266, 0.005236694908569497]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,0aN7VWwp4g,Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting,Precipitation Nowcasting;Video Prediction;Fourier Analysis;Loss Function,6.0,4.0,Chiu-Wai Yan;Shi Quan Foo;Van-Hoan Trinh;Dit-Yan Yeung;Ka-Hing Wong;Wai-Kin Wong,Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology,Chair Professor;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96922,,,https://openreview.net/forum?id=0aN7VWwp4g,/media/PosterPDFs/NeurIPS%202024/96922.png?t=1731480203.951872
1,52,-0.23586994,0.37846398,2,-0.09399681602352898,0.3334173716850977,"[1.658483445042575e-06, 1.0301760449183459e-26, 0.9999593594170149, 3.975245948143834e-20, 3.8982099540097025e-05]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,0bFXbEMz8e,FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions,generative models;material generation;chemistry;flow matching;large language models,6.0,4.333333333333333,Anuroop Sriram;Benjamin Kurt Miller;Ricky T. Q. Chen;Brandon M Wood,"Meta Facebook;University of Amsterdam;FAIR at Meta;FAIR Labs, Meta AI",Principal Researcher;PhD student;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96921,,,https://openreview.net/forum?id=0bFXbEMz8e,/media/PosterPDFs/NeurIPS%202024/96921.png?t=1730973273.143089
1,53,-0.15925287,-0.015642455,4,-0.21850191112381967,-0.004302541343377307,"[0.1122402139109214, 9.520332442980468e-10, 5.792766649490419e-07, 0.000447364983543358, 0.8873118408768372]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0bINeW40u4,Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning,Medical Multi-modal Alignment;Eye-gaze;Radiology,6.25,3.5,Chong Ma;Hanqi Jiang;Wenting Chen;Yiwei Li;Zihao Wu;Xiaowei Yu;Zhengliang Liu;Lei Guo;Dajiang Zhu;Tuo Zhang;Dinggang Shen;Tianming Liu;Xiang Li,"Northwest Polytechnical University Xi'an;Beijing Jiaotong University;City University of Hong Kong;University of Georgia;University of Georgia;University of Texas at Arlington, University of Texas at Arlington;University of Georgia;University of Texas at Arlington;Northwestern Polytechnical University;ShanghaiTech University;University of Georgia;Massachusetts General Hospital, Harvard University",PhD student;Undergrad student;PhD student;PhD student;PhD student;PhD student;PhD student;Assistant Professor;Associate Professor;Full Professor;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96920,,,https://openreview.net/forum?id=0bINeW40u4,
1,54,0.38273144,-0.19184409,1,0.40261197255458847,-0.08318364083571851,"[0.00010553172188101492, 0.9997525732733523, 6.387282078854181e-27, 0.00014189500476657479, 2.971731934177852e-21]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0cSQ1Sg7db,Generalization of Hamiltonian algorithms,Generalization;stochastic algorithms;concentration inequalities;PAC-Bayes,6.5,3.0,Andreas Maurer,,,https://neurips.cc/virtual/2024/poster/96919,,,https://openreview.net/forum?id=0cSQ1Sg7db,
1,55,-0.029614072,-0.05991212,0,0.04592027600134834,0.004652675863308072,"[0.949739120704459, 2.1694466676259363e-05, 5.31791964972929e-10, 0.02875290431312447, 0.021486279983948538]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0cgDDa4OFr,Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation,source distribution estimation;maximum entropy;Sliced-Wasserstein distance;empirical Bayes;simulation-based inference,5.8,2.8,Julius Vetter;Guy Moss;Cornelius Schröder;Richard Gao;Jakob H. Macke,Eberhard-Karls-Universität Tübingen;Eberhard-Karls-Universität Tübingen;University Tübingen;Eberhard-Karls-Universität Tübingen,PhD student;PhD student;Postdoc;Postdoc,https://neurips.cc/virtual/2024/poster/96918,,,https://openreview.net/forum?id=0cgDDa4OFr,/media/PosterPDFs/NeurIPS%202024/96918.png?t=1733318904.6928847
1,56,-0.041920777,-0.1336057,0,0.04592027600134834,0.004652675863308072,"[0.7238206712352738, 0.00017164591827094466, 2.1513184490631107e-13, 0.26841313063485733, 0.007594552211382607]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0d50Il6enG,Non-parametric classification via expand-and-sparsify representation,non-parametric regression;non-parametric classification;expand-and-sparsify representation;universal consistency;minimax-optimal convergence rate,6.0,3.0,Kaushik Sinha,Wichita State University,Associate Professor,https://neurips.cc/virtual/2024/poster/96917,,,https://openreview.net/forum?id=0d50Il6enG,/media/PosterPDFs/NeurIPS%202024/96917.png?t=1731697679.5420048
1,57,-0.05421332,-0.22073112,3,-0.1311631712723375,-0.28463581165563745,"[0.21018081989458215, 0.0006346498169720431, 2.5293145959971368e-18, 0.7887152364757084, 0.0004692938127373637]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,0dtA21q83C,DeNetDM: Debiasing by Network Depth Modulation,Trustworthy Machine Learning;Debiasing;Robustness,6.0,3.5,Silpa Vadakkeeveetil Sreelatha;Adarsh Kappiyath;Abhra Chaudhuri;Anjan Dutta,University of Surrey;University of Exeter;University of Surrey,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96916,,,https://openreview.net/forum?id=0dtA21q83C,/media/PosterPDFs/NeurIPS%202024/96916.png?t=1733689557.490417
1,58,-0.19589648,0.09422963,4,-0.21850191112381967,-0.004302541343377307,"[0.01734574539940661, 8.234592657572673e-14, 0.0029285060796302373, 2.514979873569191e-07, 0.9797254970228935]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0e5uOaJxo1,Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure,Graph Neural Network;Protein Sequence;Structure,5.0,3.3333333333333335,Bozhen Hu;Cheng Tan;Jun Xia;Yue Liu;Lirong Wu;Jiangbin Zheng;Yongjie Xu;Yufei Huang;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University, China;National University of Singapore;Westlake University;Westlake University;Westlake University;Zhejiang University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96915,,,https://openreview.net/forum?id=0e5uOaJxo1,/media/PosterPDFs/NeurIPS%202024/96915.png?t=1730385968.8958924
1,59,0.09615892,0.18102637,0,0.04592027600134834,0.004652675863308072,"[0.9938977845329359, 1.643325800572644e-07, 0.006006729741668643, 4.290538136549065e-07, 9.48923390016514e-05]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0feJEykDRx,Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models,spatial-temporal data mining;location-based service;check-in sequence;large language model,5.75,4.0,Letian Gong;Yan Lin;Xinyue Zhang;Yiwen Lu;Xuedi Han;Yichen Liu;Shengnan Guo;Youfang Lin;Huaiyu Wan,Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University,PhD student;PhD student;Undergrad student;Undergrad student;MS student;Associate Professor;Full Professor;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96914,,,https://openreview.net/forum?id=0feJEykDRx,/media/PosterPDFs/NeurIPS%202024/96914.png?t=1731289337.5941467
1,60,-0.013711061,-0.07216554,0,0.04592027600134834,0.004652675863308072,"[0.9461304017945044, 7.08021501013797e-05, 8.298865058434365e-11, 0.04589182991139041, 0.007906966061015298]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0jld45XGgJ,Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?,neural collapse;deep neural collapse;unconstrained features model;deep unconstrained features model;low-rank bias,6.5,3.75,Peter Súkeník;Christoph H. Lampert;Marco Mondelli,Institute of Science and Technology;Institute of Science and Technology Austria;Institute of Science and Technology Austria,PhD student;Assistant Professor;Professor,https://neurips.cc/virtual/2024/poster/96913,,,https://openreview.net/forum?id=0jld45XGgJ,
1,61,0.49365819,-0.019841706,1,0.40261197255458847,-0.08318364083571851,"[8.3351353639697e-05, 0.9999146528601249, 2.6366564700931807e-19, 1.9957862352567147e-06, 3.4263057308397865e-25]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0l9yGPTHAU,Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms,Robust Markov decision process;norm;sample complexity;strong duality,6.5,3.0,Pierre Clavier;Laixi Shi;Erwan Le Pennec;Eric Mazumdar;Adam Wierman;Matthieu Geist,"École Polytechnique;California Institute of Technology;Ecole polytechnique;Deparment of Computing + Mathematical Sciences, California Institute of Technology;California Institute of Technology;Google",PhD student;Postdoc;Full Professor;Assistant Professor;Professor;Researcher,https://neurips.cc/virtual/2024/poster/96912,,,https://openreview.net/forum?id=0l9yGPTHAU,
1,62,-0.096782275,0.2680031,2,-0.09399681602352898,0.3334173716850977,"[0.004834549546057942, 1.9946756703523662e-16, 0.9880773253054534, 1.9890990032335366e-12, 0.007088125146499437]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,0lBx844upd,ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models,network pruning;unstructured pruning;large language model;ADMM;pre-conditioned conjugate gradient;optimization,5.333333333333333,3.0,Xiang Meng;Kayhan Behdin;Haoyue Wang;Rahul Mazumder,Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology,PhD student;PhD student;PhD student;Associate Professor,https://neurips.cc/virtual/2024/poster/96911,,,https://openreview.net/forum?id=0lBx844upd,/media/PosterPDFs/NeurIPS%202024/96911.png?t=1731079283.0533488
1,63,-0.07022652,-0.30347943,3,-0.1311631712723375,-0.28463581165563745,"[0.0529787788153205, 0.0011106812629624627, 1.6900370116925454e-23, 0.9458911211944954, 1.941872722150108e-05]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,0lau89u4oE,Accelerating Non-Maximum Suppression: A Graph Theory Perspective,non-maximum suppression;object detection;graph theory,5.5,3.25,King-Siong Si;Lu Sun;Weizhan Zhang;Tieliang Gong;Jiahao Wang;Jiang Liu;Hao Sun,Xi'an Jiaotong University;Xi'an Jiaotong University;North China University of Technology;China Telecom Corporation Ltd. Data&AI Technology Company,MS student;MS student;MS student;Researcher,https://neurips.cc/virtual/2024/poster/96910,,,https://openreview.net/forum?id=0lau89u4oE,/media/PosterPDFs/NeurIPS%202024/96910.png?t=1733315333.5240822
1,64,-0.08510746,-0.26066056,3,-0.1311631712723375,-0.28463581165563745,"[0.0986930751955586, 0.00032992082896524485, 2.2444436612965276e-20, 0.9007061459475155, 0.00027085802796055744]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,0m19blQT6y,BitsFusion: 1.99 bits Weight Quantization of Diffusion Model,Diffusion;Quantization;Stable Diffusion;Low bit,5.75,4.5,Yang Sui;Yanyu Li;Anil Kag;Yerlan Idelbayev;Junli Cao;Ju Hu;Dhritiman Sagar;Bo Yuan;Sergey Tulyakov;Jian Ren,Rutgers University;Northeastern University;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Rutgers University;Snap Inc.;Snap Inc.,PhD student;PhD student;Researcher;Researcher;Researcher;Researcher;Researcher;Assistant Professor;Director of Research;Research Scientist,https://neurips.cc/virtual/2024/poster/96909,,,https://openreview.net/forum?id=0m19blQT6y,/media/PosterPDFs/NeurIPS%202024/96909.png?t=1729915675.3170154
1,65,-0.00251228,0.3769304,2,-0.09399681602352898,0.3334173716850977,"[0.0009856134483468301, 1.0350959196346143e-17, 0.9990092081460763, 2.4125382412088737e-16, 5.178405576737277e-06]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,0mRouJElbZ,ProgressGym: Alignment with a Millennium of Moral Progress,Progress Alignment;AI Alignment;Large Language Models,7.666666666666667,2.6666666666666665,Tianyi Qiu;Yang Zhang;Xuchuan Huang;Jasmine Xinze Li;Jiaming Ji;Yaodong Yang,"University of California, Berkeley;Peking University;Peking University;Peking University;Peking University;Peking University",Intern;Undergrad student;Undergrad student;Intern;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/97875,,,,/media/PosterPDFs/NeurIPS%202024/97875.png?t=1731742041.9348912
1,66,0.42614552,0.08994585,1,0.40261197255458847,-0.08318364083571851,"[0.027986402037814207, 0.9720054818462879, 2.556523729917162e-11, 8.11609033242367e-06, 7.364890696769862e-19]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0nSY8NiILP,Tight Bounds for Learning RUMs from Small Slates,discrete choice;random utility model;approximation theory,6.0,2.75,Flavio Chierichetti;Mirko Giacchini;Ravi Kumar;Alessandro Panconesi;Andrew Tomkins,Sapienza University of Rome;Sapienza University of Rome;Google;Sapienza University of Rome;Google,Full Professor;PhD student;Research Scientist;Full Professor;Researcher,https://neurips.cc/virtual/2024/poster/96908,,,https://openreview.net/forum?id=0nSY8NiILP,/media/PosterPDFs/NeurIPS%202024/96908.png?t=1732698791.0319488
1,67,0.25132486,-0.20319358,1,0.40261197255458847,-0.08318364083571851,"[0.007100953008434184, 0.9802795209818397, 7.733591691791306e-24, 0.01261952600968582, 4.0194463962538063e-14]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0nzKznCjFG,Private and Personalized Frequency Estimation in a Federated Setting,federated learning;personalization;privacy,5.75,3.0,Amrith Setlur;Vitaly Feldman;Kunal Talwar,Carnegie Mellon University;Apple AI Research;Apple,PhD student;Research Scientist;Research Scientist,https://neurips.cc/virtual/2024/poster/96907,,,https://openreview.net/forum?id=0nzKznCjFG,
1,68,-0.18157998,0.03947093,4,-0.21850191112381967,-0.004302541343377307,"[0.035447255799585076, 6.525401405020722e-12, 5.1174239237968217e-05, 9.863040891907582e-06, 0.9644917069137597]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0o7Rd5jngV,Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling,Transformer;expressive power;theoretical insights,6.333333333333333,3.0,Mingze Wang;Weinan E,Peking University;Peking University,PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96906,,,https://openreview.net/forum?id=0o7Rd5jngV,
1,69,-0.12251995,-0.049827244,4,-0.21850191112381967,-0.004302541343377307,"[0.4109120240574529, 9.400013057134155e-08, 2.026991530796236e-08, 0.007406527078839336, 0.5816813345936619]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0o9E8AsFgW,DarkSAM: Fooling Segment Anything Model to Segment Nothing,Segment Anything Model;Adversarial Example,6.333333333333333,4.0,Ziqi Zhou;Yufei Song;Minghui Li;Shengshan Hu;Xianlong Wang;Leo Yu Zhang;Dezhong Yao;Hai Jin,Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Griffith University;Huazhong University of Science and Technology;Huazhong University of Science and Technology,PhD student;PhD student;Assistant Professor;Associate Professor;PhD student;Researcher;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96905,,,https://openreview.net/forum?id=0o9E8AsFgW,
1,70,-0.18423451,0.25213403,2,-0.09399681602352898,0.3334173716850977,"[0.0006910578260924498, 5.204461105765133e-19, 0.9776187883273546, 4.699011183152252e-13, 0.02169015384608309]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,0oUutV92YF,ProtGO: Function-Guided Protein Modeling for Unified Representation Learning,Teacher-student;Knowledge Distillation;Protein Function,5.666666666666667,3.6666666666666665,Bozhen Hu;Cheng Tan;Yongjie Xu;Zhangyang Gao;Jun Xia;Lirong Wu;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University;Westlake University, China;Westlake University, China;Westlake University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96904,,,https://openreview.net/forum?id=0oUutV92YF,/media/PosterPDFs/NeurIPS%202024/96904.png?t=1730386167.5899446
1,71,-0.04843812,0.4040603,2,-0.09399681602352898,0.3334173716850977,"[0.00014712045432586855, 1.648419687768669e-20, 0.9998483929645298, 2.4939386452028257e-18, 4.486581144363389e-06]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,0og7nmvDbe,Confidence Regulation Neurons in Language Models,LLMs;Interpretability;Mechanistic Interpretability,7.0,3.75,Alessandro Stolfo;Ben Peng Wu;Wes Gurnee;Yonatan Belinkov;Xingyi Song;Mrinmaya Sachan;Neel Nanda,"ETHZ - ETH Zurich;University of Sheffield;Massachusetts Institute of Technology;Technion, Technion;University of Sheffield;Google DeepMind;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Assistant Professor;Lecturer;Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96903,,,https://openreview.net/forum?id=0og7nmvDbe,
1,72,0.25011468,-0.18353273,1,0.40261197255458847,-0.08318364083571851,"[0.011640440433163838, 0.9741714772873222, 1.769324204810824e-22, 0.014188082279391351, 1.2260839818354404e-13]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0qb8KoPsej,Accelerating Matroid Optimization through Fast Imprecise Oracles,matroid optimization;weak-strong models;learning-augmented algorithms;algorithms with predictions;query minimization;robustness,5.5,2.75,Franziska Eberle;Felix Hommelsheim;Alexander Lindermayr;Zhenwei Liu;Nicole Megow;Jens Schlöter,Technische Universität Berlin;Universität Bremen;Universität Bremen;Universität Bremen;Universität Bremen,Postdoc;Postdoc;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96902,,,https://openreview.net/forum?id=0qb8KoPsej,
1,73,0.24778247,-0.18444899,1,0.40261197255458847,-0.08318364083571851,"[0.012346833246183778, 0.9723062444888793, 1.8050553379002336e-22, 0.015346922264781812, 1.5532078837784284e-13]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0rl5vWOzRU,Score-Optimal Diffusion Schedules,Diffusion model;adaptive schedule;Annealed Langevin,6.0,3.0,Christopher Williams;Andrew Campbell;Arnaud Doucet;Saifuddin Syed,University of Oxford;University of Oxford;University of Oxford;University of Oxford,PhD student;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96901,,,https://openreview.net/forum?id=0rl5vWOzRU,
1,74,-0.17648138,-0.41862112,3,-0.1311631712723375,-0.28463581165563745,"[0.011113125040745405, 0.00013548861360206427, 1.3825347979630302e-29, 0.9887485899551346, 2.7963905179526303e-06]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,0sJBW05a2W,3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration,Point Cloud Registration;Focus and Matching,5.666666666666667,4.333333333333333,Liyuan Zhang;Le Hui;qi liu;Bo Li;Yuchao Dai,Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwestern Polytechnical University Xi'an;Northwestern Polytechnical University,MS student;Associate Professor;Researcher;Associate Professor;Professor,https://neurips.cc/virtual/2024/poster/96900,,,https://openreview.net/forum?id=0sJBW05a2W,/media/PosterPDFs/NeurIPS%202024/96900.png?t=1731333373.8074756
1,75,-0.16704087,-0.3598848,3,-0.1311631712723375,-0.28463581165563745,"[0.018451430770640737, 6.20226902770278e-05, 1.2418350903778268e-25, 0.9814509349183721, 3.561162071014226e-05]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,0sycTGl4In,4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization,Dynamic Novel View Synthesis;4D Gaussian splatting;Sparse reconstruction;in-the-wild,5.333333333333333,4.666666666666667,Mijeong Kim;Jongwoo Lim;Bohyung Han,Seoul National University;Seoul National University,Full Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96899,,,https://openreview.net/forum?id=0sycTGl4In,/media/PosterPDFs/NeurIPS%202024/96899.png?t=1733712090.5881364
1,76,0.61073065,0.018717432,1,0.40261197255458847,-0.08318364083571851,"[2.5375689454557664e-06, 0.9999974361486483, 2.937117193399011e-20, 2.6282406398326138e-08, 6.782642316171068e-33]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,0uGlKYS7a2,Maximizing utility in multi-agent environments by anticipating the behavior of other learners,Game Theory; no regret; learning theory;,5.5,3.25,Angelos Assos;Yuval Dagan;Constantinos Costis Daskalakis,Massachusetts Institute of Technology;Massachusetts Institute of Technology,MS student;Full Professor,https://neurips.cc/virtual/2024/poster/96898,,,https://openreview.net/forum?id=0uGlKYS7a2,/media/PosterPDFs/NeurIPS%202024/96898.png?t=1731753379.9098587
1,77,-0.07488669,0.3827278,2,-0.09399681602352898,0.3334173716850977,"[0.00013023081216295855, 1.2267676376662749e-20, 0.9998514042450997, 9.946609008659554e-18, 1.8364942737468188e-05]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,0uXtFk5KNJ,BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models,block coordinate descent;large language models,5.25,3.75,Qijun Luo;Hengxu Yu;Xiao Li,"The Chinese University of Hong Kong, Shenzhen;The Chinese University of Hong Kong, Shenzhen;Chinese University of Hong Kong Shen Zhen",PhD student;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96897,,,https://openreview.net/forum?id=0uXtFk5KNJ,/media/PosterPDFs/NeurIPS%202024/96897.png?t=1733743857.9232197
1,78,0.022653038,0.24370801,2,-0.09399681602352898,0.3334173716850977,"[0.3358917566335536, 4.316739758147992e-11, 0.6620296238396164, 1.7513685342064208e-09, 0.002078617732294135]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,0zFVhMBZHJ,Mixture of Tokens: Continuous MoE through Cross-Example Aggregation,LLM;Mixture of Experts;MoE;conditional computation;fully-differentiable;language modeling,6.0,3.6666666666666665,Szymon Antoniak;Michał Krutul;Maciej Pióro;Jakub Krajewski;Jan Ludziejewski;Kamil Ciebiera;Krystian Król;Tomasz Odrzygóźdź;Marek Cygan;Sebastian Jaszczur,IDEAS NCBR Sp.;IDEAS NCBR Sp.;University of Warsaw;University of Warsaw;IDEAS NCBR Sp.;University of Warsaw;IDEAS NCBR;Nomagic;University of Warsaw,PhD student;Researcher;PhD student;PhD student;Intern;MS student;Postdoc;Founder / CTO;PhD student,https://neurips.cc/virtual/2024/poster/96896,,,https://openreview.net/forum?id=0zFVhMBZHJ,/media/PosterPDFs/NeurIPS%202024/96896.png?t=1730308223.324062
1,79,0.24368975,0.18879418,0,0.04592027600134834,0.004652675863308072,"[0.9996235026270697, 0.00017798774783134985, 0.00019780860665985324, 6.995134340310877e-07, 1.5050052029445228e-09]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,0zWzJj6lO3,Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents,cooperative AI;AI safety;LLM agents;cognitive science;language model evaluation;dynamic evaluation;alignment;agency;evolving benchmarks;multi-agent interactions,5.75,3.5,Giorgio Piatti;Zhijing Jin;Max Kleiman-Weiner;Bernhard Schölkopf;Mrinmaya Sachan;Rada Mihalcea,Common Sense Machines;University of Michigan;Swiss Federal Institute of Technology,Principal Researcher;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96895,,,https://openreview.net/forum?id=0zWzJj6lO3,
1,80,-0.16938657,-0.05973538,4,-0.21850191112381967,-0.004302541343377307,"[0.14469757949813075, 6.007240228714849e-09, 1.6347392849906497e-08, 0.003671699325283096, 0.8516306988219531]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,0zfUiSX5si,AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases,De Novo Peptide sequencing;Proteomics;Mass Spectrum,5.333333333333333,3.0,Jun Xia;Shaorong Chen;Jingbo Zhou;Xiaojun Shan;Wenjie Du;Zhangyang Gao;Cheng Tan;Bozhen Hu;Jiangbin Zheng;Stan Z. Li,"Westlake University, China;Westlake University;Jilin University;University of Electronic Science and Technology of China;University of Science and Technology of China;Westlake University, China;Zhejiang University & Westlake University;Westlake University;Westlake University;Westlake University",PhD student;PhD student;Undergrad student;Undergrad student;Assistant Professor;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96894,,,https://openreview.net/forum?id=0zfUiSX5si,
1,81,-0.25151917,-0.28693447,3,-0.1311631712723375,-0.28463581165563745,"[0.038626410785205206, 5.19288625174458e-07, 4.1851696382379185e-19, 0.9530239884999264, 0.008349081426243183]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,105ZuvpdyW,SegVol: Universal and Interactive Volumetric Medical Image Segmentation,Volumetric Medical Image Segmentation;3D Segmentation Foundation Model;Universal and Interactive 3D Segmentation,7.666666666666667,4.333333333333333,Yuxin Du;Fan BAI;Tiejun Huang;Bo Zhao,Beijing Academy of Artificial Intelligence;The Chinese University of Hong Kong;Peking University;BAAI,Intern;PhD student;Full Professor;Principal Researcher,https://neurips.cc/virtual/2024/poster/96893,,,https://openreview.net/forum?id=105ZuvpdyW,/media/PosterPDFs/NeurIPS%202024/96893.png?t=1731410503.871179
1,82,0.04577409,-0.24324691,3,-0.1311631712723375,-0.28463581165563745,"[0.16203526820312875, 0.04119355474554887, 1.7574062786915264e-21, 0.7967702054317503, 9.71619572027632e-07]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,1067784F6e,Data Distribution Valuation,Data distribution valuation;Huber model;Maximum mean discrepancy,6.333333333333333,4.333333333333333,Xinyi Xu;Shuaiqi Wang;Chuan-Sheng Foo;Bryan Kian Hsiang Low;Giulia Fanti,"National University of Singapore;Carnegie Mellon University;Institute for Infocomm Research, A*STAR;National University of Singapore;Carnegie Mellon University",PhD student;PhD student;Principal Scientist;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96892,,,https://openreview.net/forum?id=1067784F6e,/media/PosterPDFs/NeurIPS%202024/96892.png?t=1731176029.7581189
1,83,-0.22563006,-0.049784996,4,-0.21850191112381967,-0.004302541343377307,"[0.03140731915304705, 5.89550850682295e-11, 8.650930869747344e-08, 0.0004960609616575806, 0.9680965333170316]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,12A1RT1L87,Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?,Dataset Condensation;Dataset Distillation,5.666666666666667,3.6666666666666665,Lingao Xiao;Yang He,"School of Computer Science and  Engineering, Nanyang Technological University;Institute of High Performance Computing, Singapore, A*STAR",Undergrad student;Researcher,https://neurips.cc/virtual/2024/poster/96891,,,https://openreview.net/forum?id=12A1RT1L87,/media/PosterPDFs/NeurIPS%202024/96891.png?t=1731138766.8349779
1,84,-0.20074943,0.040258985,4,-0.21850191112381967,-0.004302541343377307,"[0.02114015665756624, 1.4318886719844231e-12, 6.620649787795047e-05, 5.345058890501094e-06, 0.9787882917842334]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,135eKqDoRR,Bayesian-guided Label Mapping for Visual Reprogramming,visual reprogramming;adversarial reprogramming;output label mapping;Bayesian probability,7.25,4.0,Chengyi Cai;Zesheng Ye;Lei Feng;Jianzhong Qi;Feng Liu,University of Melbourne;Singapore University of Technology and Design;University of Melbourne;University of Melbourne,PhD student;Assistant Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96890,,,https://openreview.net/forum?id=135eKqDoRR,
1,85,-0.1496939,0.30529067,2,-0.09399681602352898,0.3334173716850977,"[0.0002099634238465346, 3.825363432793819e-20, 0.9983741504313117, 3.7223493715876405e-15, 0.0014158861448380763]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,14hLJr6kZ3,Enhancing Domain Adaptation through Prompt Gradient Alignment,transfer learning; domain adaptation; prompt-tuning,6.25,3.25,Hoang Phan;Tung Lam Tran;Quyen Tran;Trung Le,VinAi Research;VinAI Research;Monash University;New York University,Research resident;Research Resident;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96889,,,https://openreview.net/forum?id=14hLJr6kZ3,/media/PosterPDFs/NeurIPS%202024/96889.png?t=1732036918.0147438
1,86,0.2630342,0.051892787,0,0.04592027600134834,0.004652675863308072,"[0.8969095586566842, 0.10243913673353214, 1.938726808424085e-09, 0.0006513025065655928, 1.6449137266308135e-10]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,15460JjocO,Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners,multi-agent;reinforcement learning;robustness;diversity;specialization,7.0,3.6666666666666665,Rujikorn Charakorn;Poramate Manoonpong;Nat Dilokthanakul,Sakana AI;Vidyasirimedhi Institute of Science and Technology;King Mongkut's Institute of Technology Ladkrabang,Intern;Full Professor;Lecturer,https://neurips.cc/virtual/2024/poster/96888,,,https://openreview.net/forum?id=15460JjocO,/media/PosterPDFs/NeurIPS%202024/96888.png?t=1731395258.7214391
1,87,0.61719507,-0.024593957,1,0.40261197255458847,-0.08318364083571851,"[8.093963814521072e-07, 0.9999991576243146, 7.086826132347183e-23, 3.297930387492487e-08, 5.149691432842976e-34]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,15Jm9v7wCo,No-Regret Learning for Fair Multi-Agent Social Welfare Optimization,Online Learning;Nash Social Welfare,5.666666666666667,3.3333333333333335,Mengxiao Zhang;Ramiro Deo-Campo Vuong;Haipeng Luo,University of Southern California;University of Southern California,Undergrad student;Associate Professor,https://neurips.cc/virtual/2024/poster/96887,,,https://openreview.net/forum?id=15Jm9v7wCo,
1,88,-0.14552048,-0.15470643,0,0.04592027600134834,0.004652675863308072,"[0.45793841257278, 3.1448123855099404e-06, 7.461212352729404e-13, 0.3358936397246549, 0.20616480288943348]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,15PS30UOUp,Kuro Siwo: 33 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping,Synthetic Aperture Radar;SAR;Deep Learning;Remote Sensing;Floods;dataset,6.75,3.75,Nikolaos Ioannis Bountos;Maria Sdraka;Angelos Zavras;Andreas Karavias;Ilektra Karasante;Themistocles Herekakis;Angeliki Thanasou;Dimitrios Michail;Ioannis Papoutsis,National Observatory of Athens;National Observatory of Athens;Harokopio University;The Centre for Research & Technology;National Observatory of Athens ;National Observatoty of Athens;National Observatory of Athens;Harokopio University;National Technical University of Athens,PhD student;Researcher;PhD student;Researcher;Researcher;Researcher;Researcher;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97874,,,,
1,89,0.004352061,-0.07103703,0,0.04592027600134834,0.004652675863308072,"[0.9514458824083626, 0.0001488053151495698, 4.8707978743787935e-11, 0.04525775727218013, 0.003147554955599698]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,164QnJsYjF,Dense Associative Memory Through the Lens of Random Features,Associative Memory;Kernels;Random Features;Hopfield Network,6.0,3.0,Benjamin Hoover;Duen Horng Chau;Hendrik Strobelt;Parikshit Ram;Dmitry Krotov,International Business Machines;International Business Machines;International Business Machines;Massachusetts Institute of Technology;Georgia Institute of Technology,AI Research Engineer;Principal Researcher;Principal Researcher;Researcher;Full Professor,https://neurips.cc/virtual/2024/poster/96886,,,https://openreview.net/forum?id=164QnJsYjF,/media/PosterPDFs/NeurIPS%202024/96886.png?t=1733846086.053208
1,90,-0.31772932,0.41427824,2,-0.09399681602352898,0.3334173716850977,"[7.08564833781896e-08, 1.5897944191070508e-31, 0.9999969244166157, 3.4570802954802753e-23, 3.0047269011291436e-06]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,168NLzTpw8,Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation,Vision-Language;Region-Level Understanding;Multimodal Large Language Model,5.75,3.75,Yaoyuan Liang;Zhuojun Cai;Jian Xu;Guanbo Huang;Yiran Wang;Xiao Liang;Jiahao Liu;Ziran Li;Jingang Wang;Shao-Lun Huang,"Tsinghua Shenzhen International Graduate School, Tsinghua University;Microsoft;University of Electronic Science and Technology of China;Tsinghua University;Tsinghua University;Meituan;Meituan;Tsinghua University",PhD student;Intern;Undergrad student;MS student;MS student;Researcher;Researcher;Associate Professor,https://neurips.cc/virtual/2024/poster/96885,,,https://openreview.net/forum?id=168NLzTpw8,
1,91,-0.118134014,0.26676714,2,-0.09399681602352898,0.3334173716850977,"[0.002711713876994497, 3.5838605515922544e-17, 0.9882559526268964, 1.0411608362180484e-12, 0.009032333495068172]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,181llen2gw,A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks,Vision-Language Model;Fairness;Debias,6.333333333333333,3.6666666666666665,Hoin Jung;Taeuk Jang;Xiaoqian Wang,Purdue University;Purdue University;Purdue University,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96884,,,https://openreview.net/forum?id=181llen2gw,/media/PosterPDFs/NeurIPS%202024/96884.png?t=1731379505.2628894
1,92,-0.19037005,0.30377576,2,-0.09399681602352898,0.3334173716850977,"[6.573092556070265e-05, 1.1935295145865115e-21, 0.9984328190596045, 9.465417420060055e-16, 0.0015014500148337734]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,18FGRNd0wZ,Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation,tokenization of crystals;language models;materials generation,6.0,3.5,Keqiang Yan;Xiner Li;Hongyi Ling;Kenna Ashen;Carl Edwards;Raymundo Arroyave;Marinka Zitnik;Heng Ji;Xiaofeng Qian;Xiaoning Qian;Shuiwang Ji,"Texas A&M University;Texas A&M University - College Station;Texas A&M University - College Station;Texas A&M University - College Station;Genentech;Texas A&M University Main Campus;Harvard University;University of Illinois, Urbana-Champaign;Texas A&M University;Texas A&M;Texas A&M University",PhD student;PhD student;PhD student;PhD student;Intern;Assistant Professor;Full Professor;Associate Professor;Full Professor;Professor,https://neurips.cc/virtual/2024/poster/96883,,,https://openreview.net/forum?id=18FGRNd0wZ,/media/PosterPDFs/NeurIPS%202024/96883.png?t=1733428872.6393995
1,93,-0.18803668,0.09546091,4,-0.21850191112381967,-0.004302541343377307,"[0.021280650605673163, 1.4204124879459025e-13, 0.0029688543295641107, 2.9713394697505444e-07, 0.9757501979306737]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,18RdkSv9h9,FINALLY: fast and universal speech enhancement with studio-like quality,speech enhancement; generative models,6.5,4.75,Nicholas Babaev;Kirill Tamogashev;Azat Saginbaev;Ivan Shchekotov;Hanbin Bae;Hosang Sung;WonJun Lee;Hoon-Young Cho;Pavel Andreev,"Samsung;Skolkovo Institute of Science and Technology;Moscow Institute of Physics and Technology;Samsung;Samsung;Samsung;Higher School of Economics, Higher School of Economics",Researcher;MS student;MS student;Principal Researcher;Researcher;Vice President;MS student,https://neurips.cc/virtual/2024/poster/96882,,,https://openreview.net/forum?id=18RdkSv9h9,/media/PosterPDFs/NeurIPS%202024/96882.png?t=1731683595.700073
1,94,0.32727078,-0.11709024,1,0.40261197255458847,-0.08318364083571851,"[0.0037048616339198626, 0.9952801768622849, 1.8818125944060974e-20, 0.0010149615037950335, 1.5803896390079842e-16]","[0.016431530507796437, 0.012190357885548503]",0.18700354592339147,1ATLLgvURu,Learning-Augmented Priority Queues,learning-augmented algorithms;algorithms with predictions;priority queue;shortest paths;Dijkstra,5.75,4.25,Ziyad Benomar;Christian Coester,University of Oxford,Associate Professor,https://neurips.cc/virtual/2024/poster/96881,,,https://openreview.net/forum?id=1ATLLgvURu,
1,95,0.3095995,0.5030761,2,-0.09399681602352898,0.3334173716850977,"[0.029155801384018333, 1.2770913460913923e-11, 0.9708441986032086, 6.251903659179134e-18, 1.9500194566861426e-15]","[0.018617896761905145, 0.005354280534077541]",0.18728113727674375,1BZKqZphsW,Risk-Averse Fine-tuning of Large Language Models,Risk Averse Reinforcement Learning;Large Language Model Finetuning,5.8,3.2,Sapana Chaudhary;Ujwal Dinesha;Dileep Kalathil;Srinivas Shakkottai,Texas A&M University;Texas A&M University - College Station;Texas A&M University;Texas A&M,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96880,,,https://openreview.net/forum?id=1BZKqZphsW,/media/PosterPDFs/NeurIPS%202024/96880.png?t=1733328781.5713553
1,96,-0.26364937,-0.38828564,3,-0.1311631712723375,-0.28463581165563745,"[0.008661501142037798, 2.1818333532394323e-06, 8.331607810400578e-26, 0.9912724777111682, 6.383931344081974e-05]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,1CssOqRYyz,Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds,compression;point cloud;diffusion,4.0,4.0,Kai Liu;Kang You;Pan Gao,"Nanjing University of Aeronautics and Astronautics;Nanjing university;Nanjing University of Aeronautics and Astronautics, Tsinghua University",MS student;PhD student;Associate Professor,,,,,
1,97,-0.25224024,-0.31188005,3,-0.1311631712723375,-0.28463581165563745,"[0.024928977427275574, 7.867578056501439e-07, 9.166614095443392e-21, 0.9726624020724675, 0.002407833742451224]","[0.01476036871646432, 0.0071260030888920245]",0.1654539286072824,1Du3mMP5YN,Learning to Shape In-distribution Feature Space for Out-of-distribution Detection,Out-of-distribution Detection,5.75,4.0,Yonggang Zhang;Jie Lu;Bo Peng;Zhen Fang;Yiu-ming Cheung,Hong Kong Baptist University;University of Technology Sydney;University of Technology Sydney,Postdoc;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96879,,,https://openreview.net/forum?id=1Du3mMP5YN,/media/PosterPDFs/NeurIPS%202024/96879.png?t=1731745181.7993424
1,98,-0.30068702,-0.14781809,4,-0.21850191112381967,-0.004302541343377307,"[0.04518947432339692, 2.6401935629135715e-10, 1.1601356334160247e-10, 0.02975578212746277, 0.9250547431691074]","[0.004761144359449799, 0.006602778410805141]",0.21601783132946334,1ELFGSNBGC,Multiview Scene Graph,scene representation; spatial understanding; place recognition; object correspondence; scene graph,5.25,3.25,Juexiao Zhang;Gao Zhu;Sihang Li;Xinhao Liu;Haorui Song;Xinran Tang;Chen Feng,New York University;New York University;New York University;New York University;New York University;New York University;New York University,PhD student;MS student;PhD student;PhD student;MS student;MS student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96878,,,https://openreview.net/forum?id=1ELFGSNBGC,/media/PosterPDFs/NeurIPS%202024/96878.png?t=1731728482.5838113
1,99,-0.09486352,0.005280091,0,0.04592027600134834,0.004652675863308072,"[0.5016294340281147, 3.360494247626654e-08, 1.6079477258197025e-06, 0.0009014394910597637, 0.49746748492815723]","[0.01464062962259357, 0.015246489875024563]",0.24424355686311905,1F32iCJFfa,Schrodinger Bridge Flow for Unpaired Data Translation,unpaired data translation;diffusion models;Schrodinger bridge;bridge matching;stochastic interpolant;flow matching,6.5,4.0,Valentin De Bortoli;Iryna Korshunova;Andriy Mnih;Arnaud Doucet,University of Oxford;Google DeepMind;Google DeepMind;University of Oxford,Postdoc;Researcher;Research Scientist;Full Professor,https://neurips.cc/virtual/2024/poster/96877,,,https://openreview.net/forum?id=1F32iCJFfa,/media/PosterPDFs/NeurIPS%202024/96877.png?t=1731688420.732189
2,0,0.08799766,-0.06060414,0,0.06416460631639377,0.015145813478756244,"[0.8881701377600452, 0.007392061812342354, 1.0765705261906944e-11, 0.10419012594449811, 0.0002476744723485298]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,00Sx577BT3,The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning,numerical simulations;fluid-dynamics;partial differential equations;operator learning,6.666666666666667,3.6666666666666665,Ruben Ohana;Michael McCabe;Lucas Thibaut Meyer;Rudy Morel;Fruzsina Julia Agocs;Miguel Beneitez;Marsha Berger;Blakesley Burkhart;Stuart B. Dalziel;Drummond Buschman Fielding;Daniel Fortunato;Jared A. Goldberg;Keiya Hirashima;Yan-Fei Jiang;Rich Kerswell;Suryanarayana Maddu;Jonah M. Miller;Payel Mukhopadhyay;Stefan S. Nixon;Jeff Shen;Romain Watteaux;Bruno Régaldo-Saint Blancard;François Rozet;Liam Holden Parker;Miles Cranmer;Shirley Ho,"Flatiron Institute;University of Colorado, Boulder;INRIA;Flatiron Institute;Flatiron Institute;University of Cambridge;Flatiron Institute;Rutgers University;University of Cambridge;Simons Foundation;Flatiron Institute;Flatiron Institute;Simons Foundation;University of Cambridge;Flatiron Institute/Simons Foundation;Los Alamos National Laboratory;University of California, Berkeley;University of Cambridge;Princeton University;CEA;Flatiron Institute;Flatiron Institute;Flatiron Institute;University of Cambridge;Carnegie Mellon University;The University of Tokyo",Postdoc;PhD student;PhD student;Postdoc;Postdoc;Postdoc;Full Professor;Assistant Professor;Director of the GK Batchelor Laboratory;Postdoc;Researcher;Postdoc;Researcher;Full Professor;Postdoc;Researcher;Postdoc;PhD student;PhD student;Researcher;Postdoc;Intern;Researcher;Assistant Professor;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/97882,,,,
2,1,-0.08406016,0.2851326,2,-0.09636739540443189,0.3320709647221278,"[0.00246237659284696, 2.259363797755776e-15, 0.9955517811713654, 5.735722815336125e-09, 0.0019858365000627065]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,00uVk06eVK,On the Noise Robustness of In-Context Learning for Text Generation,In-Context Learning;Large Language Models;Noise Robustness,6.333333333333333,3.0,Hongfu Gao;Feipeng Zhang;Wenyu Jiang;Jun Shu;Feng Zheng;Hongxin Wei,Xi'an Jiaotong University;Xi'an Jiaotong University;Nanjing University;Xi'an Jiaotong University;Southern University of Science and Technology;Southern University of Science and Technology,MS student;Full Professor;PhD student;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96962,,,https://openreview.net/forum?id=00uVk06eVK,/media/PosterPDFs/NeurIPS%202024/96962.png?t=1731587881.4159098
2,2,-0.16364236,-0.11411294,4,-0.20935347267655594,-0.000529932480074861,"[0.17068927054031527, 1.1419139418234508e-06, 1.4173511114438993e-10, 0.217261900788135, 0.6120476866158728]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,01I55gys19,Few-Class Arena: A Benchmark for Efficient Vision Model Selection and Dataset Difficulty,few-class;efficiency;neural network;convolutional neural network;transformer;dataset difficulty measurement;scaling law,5.0,3.3333333333333335,Bryan Bo Cao;Lawrence O'Gorman;Michael Coss;Shubham Jain,Nokia networks GmbH;State University of New York at Stony Brook,Intern;Assistant Professor,,,,,
2,3,0.07371062,-0.27021888,3,-0.12954866399913614,-0.26501765285515333,"[0.1377688638649481, 0.22117385515817378, 1.9298446046837924e-23, 0.6410571061532393, 1.748236387552861e-07]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,01XV5Za56k,Testing Calibration in Nearly-Linear Time,Calibration;Property testing;Linear programming,6.25,3.25,Lunjia Hu;Arun Jambulapati;Kevin Tian;Chutong Yang,Stanford University;Stanford University;Stanford University;University of Texas at Austin,PhD student;PhD student;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96961,,,https://openreview.net/forum?id=01XV5Za56k,
2,4,-0.1284643,0.3103237,2,-0.09636739540443189,0.3320709647221278,"[0.00021018734719473487, 5.819405069743701e-18, 0.9992604623387201, 1.9158376196471484e-10, 0.0005293501225013094]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,01lhHg8H9p,GLBench: A Comprehensive Benchmark for Graph with Large Language Models,Graph learning;Large Language Model;Zero-Shot,6.75,4.0,Yuhan Li;Peisong Wang;Xiao Zhu;Aochuan Chen;Haiyun Jiang;Deng Cai;Victor Wai Kin Chan;Jia Li,"Hong Kong University of Science and Technology;Tsinghua University;Beijing University of Posts and Telecommunications;Hong Kong University of Science and Technology;Tencent AI Lab;Tencent AI Lab;Shenzhen International Graduate School, Tsinghua University;Hong Kong University of Science and Technology",PhD student;MS student;Undergrad student;PhD student;Researcher;Research Scientist;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97881,,,,/media/PosterPDFs/NeurIPS%202024/97881.png?t=1731478194.2539835
2,5,-0.23808402,0.26056772,2,-0.09636739540443189,0.3320709647221278,"[2.823979979552959e-05, 1.272115379048074e-19, 0.9954351604723872, 3.7247248673008906e-10, 0.004536599355344814]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,01qa1ZJs65,Bridge the Modality and Capability Gaps in Vision-Language Model Selection,Vision-Language Model;Model Selection;Zero-Shot Image Classification,5.25,4.0,Chao Yi;Yuhang He;De-Chuan Zhan;Han-Jia Ye,Nanjing University;Nanjing University;Nanjing University;Nanjing University,MS student;Undergrad student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96960,,,https://openreview.net/forum?id=01qa1ZJs65,/media/PosterPDFs/NeurIPS%202024/96960.png?t=1731123927.9174762
2,6,-0.10493148,-0.30384988,3,-0.12954866399913614,-0.26501765285515333,"[0.05153097800368383, 0.0007303298415682991, 1.3486135685494964e-22, 0.9476959072545066, 4.278490024119052e-05]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,01s5ODIHKd,FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space,deep watermarking;latent frequency optimization,5.5,3.75,YiYang Guo;Ruizhe Li;Mude Hui;Hanzhong Allan Guo;Chen Zhang;Chuangjian Cai;Le Wan;Shangfei Wang,"University of Science and Technology of China;University of California, Santa Cruz;Renmin University of China;Tsinghua University;University of Science and Technology of China;University of Science and Technology of China",MS student;PhD student;MS student;PhD student;Full Professor;PhD student,https://neurips.cc/virtual/2024/poster/96959,,,https://openreview.net/forum?id=01s5ODIHKd,/media/PosterPDFs/NeurIPS%202024/96959.png?t=1730176108.8718698
2,7,-0.295713,-0.42771262,3,-0.12954866399913614,-0.26501765285515333,"[0.0037644238309774095, 5.544786118682879e-06, 1.1202342976133222e-27, 0.9962280764027758, 1.9549801280019798e-06]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,02CIZ8qeDc,PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection,3D anomaly detection;Zero-shot 3D anomaly detection,6.0,3.6666666666666665,Qihang Zhou;Jiangtao Yan;Shibo He;Wenchao Meng;Jiming Chen,Zhejiang University;Zhejiang University;Zhejiang University;Zhejiang University,PhD student;MS student;Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96958,,,https://openreview.net/forum?id=02CIZ8qeDc,/media/PosterPDFs/NeurIPS%202024/96958.png?t=1731476864.9817398
2,8,-0.3188932,-0.023905918,4,-0.20935347267655594,-0.000529932480074861,"[0.0009003656091028176, 6.981121751992841e-13, 6.77522814269347e-06, 0.0004146123140228256, 0.9986782468480335]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,02HWT9c4Lp,Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion,Semantic Scene completion，Voxel Proposal，Knowledge Distillation,5.5,4.0,Lubo Wang;Di Lin;Kairui Yang;Ruonan Liu;Qing Guo;Wuyuan Xie;Miaohui Wang;Lingyu Liang;Yi Wang;Ping Li,"Tianjin University;Tianjin University;Tianjin University;Tianjin University; Agency for Science, Technology and Research (A*STAR));Department of Software Engineering, Shenzhen University;Shenzhen University;South China University of Technology;Shenzhen University;The Hong Kong Polytechnic University",MS student;Associate Professor;PhD student;Associate Professor;Researcher;Associate Professor;Associate Professor;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96957,,,https://openreview.net/forum?id=02HWT9c4Lp,/media/PosterPDFs/NeurIPS%202024/96957.png?t=1731159292.6143699
2,9,0.52375084,0.03593809,1,0.3965452440744716,-0.08384307613416417,"[3.727518163909915e-05, 0.9999621521209727, 6.093559571860015e-17, 5.726973882819023e-07, 3.1863925344756653e-21]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,02r24A8doi,Achieving Constant Regret in Linear Markov Decision Processes,Reinforcement learning;Constant regret;Misspecified linear MDP,5.25,2.75,Weitong Zhang;Zhiyuan Fan;Jiafan He;Quanquan Gu,"Massachusetts Institute of Technology;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles",PhD student;PhD student;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96956,,,https://openreview.net/forum?id=02r24A8doi,
2,10,-0.24769914,0.06194072,4,-0.20935347267655594,-0.000529932480074861,"[0.0019169464331997546, 3.2332891447701556e-13, 0.0007372972029302228, 4.0772778381244525e-05, 0.9973049835851655]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,04EC4ZnZJj,MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers,transformer architecture;large language model;computational complexity reduction,6.0,3.5,Ning Ding;Yehui Tang;Haochen Qin;Zhenli Zhou;Chao Xu;Lin Li;Kai Han;Liao Heng;Yunhe Wang,"Peking University;Huawei Technologies Ltd.;Huawei Technologies Ltd.;Peking University;Peking University;Huawei Noah's Ark Lab;, Tsinghua University;Huawei Noah's Ark Lab",PhD student;Researcher;Researcher;MS student;Full Professor;Principal Researcher;Principal Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96955,,,https://openreview.net/forum?id=04EC4ZnZJj,
2,11,0.45866024,0.07679337,1,0.3965452440744716,-0.08384307613416417,"[0.0023064075872839054, 0.9976844242419768, 6.114945926007434e-13, 9.168170127813836e-06, 6.14932789963889e-17]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,06JRFVK88O,Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games,Multi-agent Reinforcement Learning;Imitation Learning,6.666666666666667,3.0,The Viet Bui;Tien Anh Mai;Thanh Hong Nguyen,Singapore Management University;University of Oregon;Singapore Management University,Assistant Professor;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96954,,,https://openreview.net/forum?id=06JRFVK88O,/media/PosterPDFs/NeurIPS%202024/96954.png?t=1731744891.8886228
2,12,-0.21952832,-0.2596673,3,-0.12954866399913614,-0.26501765285515333,"[0.037241025992044374, 5.447042368186761e-06, 9.911031546402137e-18, 0.9549702398132583, 0.007783287152328927]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,06Vt6f2js7,SyncTweedies: A General Generative Framework Based on Synchronized Diffusions,Diffusion Models;Synchronization;Texturing;3D Gaussian Splatting;Mesh;Panorama,6.666666666666667,3.6666666666666665,Jaihoon Kim;Juil Koo;Kyeongmin Yeo;Minhyuk Sung,KAIST;Adobe Systems;Korea Advanced Institute of Science & Technology;Korea Advanced Institute of Science & Technology,MS student;Intern;Undergrad student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96953,,,https://openreview.net/forum?id=06Vt6f2js7,
2,13,0.5387558,-0.021885695,1,0.3965452440744716,-0.08384307613416417,"[4.350864534460579e-06, 0.9999953629081472, 1.4097172802671735e-20, 2.862273184773614e-07, 4.977880199935938e-23]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,07N0qoaZ2L,Improved Analysis for Bandit Learning in Matching Markets,Bandits;Matching markets;Stable matching;Stable regret;Exploration and exploitation;$\alpha$-condition,5.5,3.0,Fang Kong;Zilong Wang;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;John Hopcroft Center, Shanghai Jiao Tong University",PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96952,,,https://openreview.net/forum?id=07N0qoaZ2L,/media/PosterPDFs/NeurIPS%202024/96952.png?t=1731746661.9360106
2,14,-0.31746334,-0.03755091,4,-0.20935347267655594,-0.000529932480074861,"[0.0011341840468387689, 1.7247960436342208e-12, 2.305785768740507e-06, 0.0007448575474862, 0.9981186526181816]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,08A6X7FSTs,Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text,Text-to-3D Scene Generation;Latent Diffusion Models,5.5,4.5,Xinyang Li;Zhangyu Lai;Linning Xu;Yansong Qu;Liujuan Cao;Shengchuan Zhang;Bo Dai;Rongrong Ji,Xiamen University;Xiamen University;Xiamen University;Xiamen University;Xiamen University;Shanghai AI Laboratory;Xiamen University;The Chinese University of Hong Kong,PhD student;MS student;PhD student;Full Professor;Assistant Professor;Scientist;Full Professor;Ph.D. student,https://neurips.cc/virtual/2024/poster/96951,,,https://openreview.net/forum?id=08A6X7FSTs,/media/PosterPDFs/NeurIPS%202024/96951.png?t=1732593534.8700738
2,15,0.21572201,0.15297481,0,0.06416460631639377,0.015145813478756244,"[0.9992494380884657, 0.0004816224609344884, 3.3333568862357516e-05, 0.00023461000241033534, 9.958793269546979e-07]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,08GbdALmEs,Learning Versatile Skills with Curriculum Masking,reinforcement learning;unsupervised pretraining;masked prediction;curriculum learning,5.25,3.25,Yao Tang;Zhihui Xie;Zichuan Lin;Deheng Ye;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;Tencent AI Lab;Tencent;John Hopcroft Center, Shanghai Jiao Tong University",Undergrad student;MS student;Researcher;Principal Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96950,,,https://openreview.net/forum?id=08GbdALmEs,/media/PosterPDFs/NeurIPS%202024/96950.png?t=1733319308.3295946
2,16,-0.17784788,-0.16018736,3,-0.12954866399913614,-0.26501765285515333,"[0.1592987207522484, 3.4467898058092887e-06, 1.4042264838411073e-12, 0.5704718067718455, 0.270226025684696]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,08nbMTxazb,Chicks4FreeID: A Benchmark Dataset for Chicken Re-Identification,animal re-identification;chicken re-identification;chicken dataset;re-identification dataset;benchmark dataset;closed-set re-identification;computer vision;chicken instance segmentation;poultry;livestock,4.75,4.0,Daria Kern;Tobias Schiele;Ulrich Klauck;Winfred Ingabire,Glasgow Caledonian University;Hochschule Aalen;Glasgow Caledonian University,PhD student;Full Professor;Lecturer,,,,,
2,17,0.12485067,-0.17534988,3,-0.12954866399913614,-0.26501765285515333,"[0.3369074558870707, 0.3196185622499296, 2.0311133574212868e-18, 0.3434731892419235, 7.926210759479387e-07]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,08oUnmtj8Q,FSEO: A Few-Shot Evolutionary Optimization Framework for Expensive Multi-Objective Optimization and Constrained Optimization,Expensive optimization;few-shot optimization;multi-objective optimization;constrained optimization;surrogate-assisted evolutionary optimization,4.5,3.5,Xunzhao Yu,,,,,,,
2,18,-0.045080878,-0.32160506,3,-0.12954866399913614,-0.26501765285515333,"[0.06251587050135264, 0.007802809748970739, 8.234275324763738e-25, 0.9296790833957711, 2.2363539054997086e-06]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,09RKw0vXjR,Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations,feature selection;sparse coding;dictionary learning;compressed sensing;iterative hard thresholding;pruning method,5.75,3.0,Yasutoshi Ida;Sekitoshi Kanai;Atsutoshi Kumagai;Tomoharu Iwata;Yasuhiro Fujiwara,NTT;NTT;NTT;NTT;NTT,Researcher;Researcher;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96949,,,https://openreview.net/forum?id=09RKw0vXjR,/media/PosterPDFs/NeurIPS%202024/96949.png?t=1733375377.8112724
2,19,-0.29219365,-0.1354431,4,-0.20935347267655594,-0.000529932480074861,"[0.01327733388264037, 2.893373095059983e-09, 4.1406881765208476e-10, 0.07208320896331417, 0.9146394538466036]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,09nyBqSdUz,RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance,Consistent image generation;Diverse image generation;Improve temporal-consistency;Feature injection from multiple images,5.5,4.0,Jiaojiao Fan;Haotian Xue;Qinsheng Zhang;Yongxin Chen,Georgia Institute of Technology;Georgia Institute of Technology;Georgia Institute of Technology;NVIDIA,PhD student;PhD student;Associate Professor;Research Intern,https://neurips.cc/virtual/2024/poster/96948,,,https://openreview.net/forum?id=09nyBqSdUz,/media/PosterPDFs/NeurIPS%202024/96948.png?t=1731392354.7708242
2,20,0.22983314,0.005944166,0,0.06416460631639377,0.015145813478756244,"[0.7967505565129958, 0.18834526365408708, 8.349539962631373e-11, 0.014904006256168969, 1.7349325305342636e-07]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0AumdfLzpK,A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations,Visual Reinforcement Learning;Generalization,6.0,4.0,Wonil Song;Hyesong Choi;Kwanghoon Sohn;Dongbo Min,Yonsei Univ.;Ewha Womans University;Yonsei University;Ewha Womans University,PhD student;PhD student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96947,,,https://openreview.net/forum?id=0AumdfLzpK,/media/PosterPDFs/NeurIPS%202024/96947.png?t=1732451612.1247888
2,21,-0.2313607,0.15489271,4,-0.20935347267655594,-0.000529932480074861,"[0.002077140860577757, 5.3635215182642005e-15, 0.23915977854263026, 1.683367407457116e-06, 0.7587613972293792]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0AwMciNShl,"Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality",Human evaluation;text-to-video models,5.25,4.0,Tianle Zhang;Langtian Ma;Yuchen Yan;Yuchen Zhang;Yue Yang;Ziyao Guo;Wenqi Shao;Kai Wang;Yang You;Yu Qiao;Ping Luo;Kaipeng Zhang,University of Electronic Science and Technology of China;Southern University of Science and Technology;The University of Nottingham Ningbo China;University of Electronic Science and Technology of China;Xidian University;Shanghai AI Laboratory;National University of Singapore;National University of Singapore;Shanghai AI Laboratory;The University of Hong Kong;Shanghai Jiaotong University,Undergrad student;Undergrad student;Undergrad student;Undergrad student;MS student;Researcher;PhD student;Professor;Researcher;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96946,,,https://openreview.net/forum?id=0AwMciNShl,/media/PosterPDFs/NeurIPS%202024/96946.png?t=1729079669.652648
2,22,0.44196302,-0.22339565,1,0.3965452440744716,-0.08384307613416417,"[4.337350993198081e-06, 0.9999885697820133, 1.901740380555329e-30, 7.092866993327507e-06, 9.990939380633682e-22]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0C3bLHwjsY,Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions,Online Matching;Competitive Analysis;Fairness Maximization,6.25,3.0,Will Ma;Pan Xu,Columbia University;New Jersey Institute of Technology,Assistant Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96945,,,https://openreview.net/forum?id=0C3bLHwjsY,/media/PosterPDFs/NeurIPS%202024/96945.png?t=1731641014.5806563
2,23,0.31953293,-0.23248373,1,0.3965452440744716,-0.08384307613416417,"[0.00031745065370985366, 0.9991424991594958, 1.3982936517070454e-27, 0.0005400501867938259, 5.39678839095856e-16]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0DE1dLMW2b,Quantum algorithm for large-scale market equilibrium computation,market equilibrium computation;quantum algorithm,6.0,2.75,Po-Wei Huang;Patrick Rebentrost,Centre for Quantum Technologies;National University of Singapore,Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96944,,,https://openreview.net/forum?id=0DE1dLMW2b,/media/PosterPDFs/NeurIPS%202024/96944.png?t=1731426989.5298698
2,24,0.0025802255,-0.08199731,0,0.06416460631639377,0.015145813478756244,"[0.7888294655609551, 0.0005733622071190447, 2.2533133181912863e-11, 0.20136768856941176, 0.009229483639980926]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0EfUYVMrLv,Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment,non-stationary environments;continuous distribution shift;test-time adaptation;unlabeled data,6.666666666666667,4.0,Zhen-Yu Zhang;Zhiyu Xie;Huaxiu Yao;Masashi Sugiyama,"RIKEN;Stanford University;Department of Computer Science, University of North Carolina at Chapel Hill;The University of Tokyo",Postdoc;MS student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96943,,,https://openreview.net/forum?id=0EfUYVMrLv,/media/PosterPDFs/NeurIPS%202024/96943.png?t=1731687693.6296034
2,25,0.023439856,-0.079839304,0,0.06416460631639377,0.015145813478756244,"[0.8129457956554932, 0.0011743024627179773, 1.3304121989642847e-11, 0.18207943824018635, 0.003800463628298428]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0G0VpMjKyV,Sketching for Distributed Deep Learning: A Sharper Analysis,sketching;distributed learning;federated learning;optimization,5.666666666666667,4.0,Mayank Shrivastava;Berivan Isik;Qiaobo Li;Sanmi Koyejo;Arindam Banerjee,"University of Illinois, Urbana Champaign;Stanford University;Department of Computer Science, University of Illinois at Urbana-Champaign;University of Illinois, Urbana Champaign;Google",MS student;PhD student;PhD student;Professor;Research Scientist,https://neurips.cc/virtual/2024/poster/96942,,,https://openreview.net/forum?id=0G0VpMjKyV,/media/PosterPDFs/NeurIPS%202024/96942.png?t=1733481266.9121125
2,26,-0.06371302,0.3954228,2,-0.09636739540443189,0.3320709647221278,"[0.00013397792541191837, 3.809789282794022e-19, 0.9998620356115246, 1.927396948638147e-12, 3.98646113607309e-06]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,0G5OK5vmmg,WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts,Benchmark;Large Language Models;Classical Chinese Literature and Language Arts,6.25,2.75,Jiahuan Cao;Yang Liu;Yongxin Shi;Kai Ding;Lianwen Jin,South China University of Technology;South China University of Technology;South China University of Technology;INTSIG Information;South China University of Technology,MS student;MS student;PhD student;Researcher;Professor,https://neurips.cc/virtual/2024/poster/97880,,,,/media/PosterPDFs/NeurIPS%202024/97880.png?t=1730896668.2191207
2,27,-0.2963673,0.015343715,4,-0.20935347267655594,-0.000529932480074861,"[0.0008876993981108061, 2.407328951877082e-13, 7.063118142843881e-05, 0.00011192285351112543, 0.9989297465667087]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0G8AXwtmy2,T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition,harmful dataset;harmful content detection;Vision Language Model,6.5,3.75,Chen Yeh;You-Ming Chang;Wei-Chen Chiu;Ning Yu,National Yang Ming Chiao Tung University;National Yang Ming Chiao Tung University;National Chiao Tung University,MS student;MS student;Associate Professor,https://neurips.cc/virtual/2024/poster/97879,,,,/media/PosterPDFs/NeurIPS%202024/97879.png?t=1730218737.4487233
2,28,0.08612508,0.3898904,2,-0.09636739540443189,0.3320709647221278,"[0.009665839988098812, 5.810814117559722e-14, 0.9903337809727641, 1.4983592543709223e-10, 3.788892431198853e-07]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,0Gl5WxY6es,Grounding Multimodal Large Language Models in Actions,Embodied AI;Multimodal Large Language Models;Reinforcement Learning;Imitation Learning,6.0,3.6666666666666665,Andrew Szot;Bogdan Mazoure;Harsh Agrawal;R Devon Hjelm;Zsolt Kira;Alexander T Toshev,Georgia Institute of Technology;Apple;Apple;Apple;Georgia Institute of Technology;Apple,PhD student;Research Scientist;Researcher;Researcher;Assistant Professor;research scientist,https://neurips.cc/virtual/2024/poster/96941,,,https://openreview.net/forum?id=0Gl5WxY6es,
2,29,-0.20296153,0.2345368,2,-0.09636739540443189,0.3320709647221278,"[0.0003396289310857893, 3.2214190276406225e-17, 0.9697846074552421, 1.085385873582758e-08, 0.029875752759813207]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,0Gmi8TkUC7,GenAI Arena: An Open Evaluation Platform for Generative Models,Evaluation;Benchmark;Platform;Generative Model,6.0,3.5,Dongfu Jiang;Max Ku;Tianle Li;Yuansheng Ni;Shizhuo Sun;Rongqi Fan;Wenhu Chen,Allen Institute for Artificial Intelligence;University of Waterloo;University of Waterloo;University of Toronto;NVIDIA;University of Waterloo,Intern;MS student;MS student;Undergrad student;Intern;Assistant Professor,https://neurips.cc/virtual/2024/poster/97878,,,,/media/PosterPDFs/NeurIPS%202024/97878.png?t=1730329031.3167162
2,30,-0.3021013,-0.23802479,3,-0.12954866399913614,-0.26501765285515333,"[0.022947847564826138, 1.5009911459990708e-07, 6.289860573552464e-15, 0.8947260083384533, 0.0823259939975997]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,0HRRNEAQFp,A General Protocol to Probe Large Vision Models for 3D Physical Understanding,3D physical scene understanding; Representation probing protocol; Benchmark and evaluation,6.333333333333333,4.0,Guanqi Zhan;Chuanxia Zheng;Weidi Xie;Andrew Zisserman,University of Oxford;University of Oxford;Shanghai Jiaotong University,PhD student;Postdoc;Associate Professor,https://neurips.cc/virtual/2024/poster/96940,,,https://openreview.net/forum?id=0HRRNEAQFp,/media/PosterPDFs/NeurIPS%202024/96940.png?t=1731705235.0575316
2,31,0.40233114,0.06031101,1,0.3965452440744716,-0.08384307613416417,"[0.016460409172403045, 0.9834520197451769, 3.3003744907469195e-12, 8.757107908542569e-05, 3.408673810372369e-14]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0JSKjdePGq,When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL,reinforcement learning;continuous-time,6.75,3.25,Lenart Treven;Bhavya Sukhija;Yarden As;Florian Dorfler;Andreas Krause,"Swiss Federal Institute of Technology;ETHZ - ETH Zurich;Department of Computer Science, ETHZ - ETH Zurich;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96939,,,https://openreview.net/forum?id=0JSKjdePGq,/media/PosterPDFs/NeurIPS%202024/96939.png?t=1730197260.75527
2,32,-0.31179968,-0.050893012,4,-0.20935347267655594,-0.000529932480074861,"[0.0015774082240316946, 5.297593957438278e-12, 7.056929137763034e-07, 0.0013991165476017955, 0.9970227695301552]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0KseSacluJ,CoFie: Learning Compact Neural Surface Representations with Coordinate Fields,Neural Surface Representation;Shape Auto-Decoding;Coordinate Field.,5.0,4.0,Hanwen Jiang;Haitao Yang;Georgios Pavlakos;Qixing Huang,University of Texas at Austin;The University of Texas at Austin;University of Texas at Austin;University of Texas at Austin,PhD student;PhD student;Assistant Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96938,,,https://openreview.net/forum?id=0KseSacluJ,
2,33,0.11298243,0.035079706,0,0.06416460631639377,0.015145813478756244,"[0.9894475342685441, 0.0007076722802693516, 5.470437371431171e-08, 0.009573897246115848, 0.00027084150069709855]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0KvYLaTBTE,Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference,Generative models;Reinforcement learning;Decision transformer,6.333333333333333,3.0,Deqian Kong;Dehong Xu;Minglu Zhao;Bo Pang;Jianwen Xie;Andrew Lizarraga;Yuhao Huang;Sirui Xie;Ying Nian Wu,"University of California, Los Angeles;Amazon;University of California, Los Angeles;University of California, Los Angeles;Xi'an Jiaotong University;University of California, Los Angeles;University of California, Los Angeles;UCLA",PhD student;Intern;PhD student;PhD student;PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96937,,,https://openreview.net/forum?id=0KvYLaTBTE,
2,34,-0.23456638,0.06657637,4,-0.20935347267655594,-0.000529932480074861,"[0.00262217501322797, 5.777425506493754e-13, 0.0008197581632636521, 4.4021297578124926e-05, 0.9965140455253524]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0LXotew9Du,KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization,Quantization;KV Cache;LLM Inference;Compression;Long Context Length,6.25,3.25,Coleman Richard Charles Hooper;Sehoon Kim;Hiva Mohammadzadeh;Michael W. Mahoney;Sophia Shao;Kurt Keutzer;Amir Gholami,"University of California, Berkeley;University of California, Berkeley;University of California, Berkeley;University of California, Berkeley",PhD student;PhD student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96936,,,https://openreview.net/forum?id=0LXotew9Du,
2,35,0.11017645,-0.16371755,0,0.06416460631639377,0.015145813478756244,"[0.43637866140348647, 0.1819660554273742, 1.9007048483400967e-17, 0.3816520557844549, 3.227384684613297e-06]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0Lb8vZT1DB,Reliable Learning of Halfspaces under Gaussian Marginals,reliable learning;agnostic learning;halfspace;proper leaning;statistical query,7.25,2.25,Ilias Diakonikolas;Lisheng Ren;Nikos Zarifis,"University of Wisconsin - Madison;University of Wisconsin - Madison;University of Wisconsin, Madison",Full Professor;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96935,,,https://openreview.net/forum?id=0Lb8vZT1DB,
2,36,0.1429859,0.059452157,0,0.06416460631639377,0.015145813478756244,"[0.9944110654377953, 0.0009475475508304719, 1.7901963261985798e-07, 0.004578485051556462, 6.272294018491808e-05]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0LfgE6kvKZ,Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning,Federated Learning; Model Merging,5.0,3.6666666666666665,Minghui Chen;Meirui Jiang;Xin Zhang;Qi Dou;Zehua Wang;Xiaoxiao Li,"University of British Columbia;Meta Facebook;The Chinese University of Hong Kong;University of British Columbia;University of British Columbia;Department of Computer Science and Engineering, The Chinese University of Hong Kong",PhD student;Research Scientist;Assistant Professor;Researcher;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96934,,,https://openreview.net/forum?id=0LfgE6kvKZ,/media/PosterPDFs/NeurIPS%202024/96934.png?t=1731518093.5294044
2,37,-0.040502112,0.02318828,0,0.06416460631639377,0.015145813478756244,"[0.7157650212801115, 1.8980715541241405e-06, 2.8311303318159823e-06, 0.015315366019908482, 0.268914883498094]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0Lr9HQijA1,Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations,Imprecise Label Learning,5.75,3.0,Hao Chen;Ankit Shah;Jindong Wang;Ran Tao;Yidong Wang;Xiang Li;Xing Xie;Masashi Sugiyama;Rita Singh;Bhiksha Raj,"Carnegie Mellon University;Accenture;Microsoft Research;Peking University;Microsoft Research Asia;The University of Tokyo;School of Computer Science, Carnegie Mellon University;Mohamed bin Zayed University of Artificial Intelligence",PhD student;Principal Researcher;Researcher;PhD student;Senior Principal Researcher;Full Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96933,,,https://openreview.net/forum?id=0Lr9HQijA1,/media/PosterPDFs/NeurIPS%202024/96933.png?t=1731704880.9846606
2,38,-0.06471333,0.08954511,4,-0.20935347267655594,-0.000529932480074861,"[0.3940511286013828, 2.1883352935971908e-08, 0.0008570213322843219, 0.0012644869530289103, 0.603827341229951]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0MXzbAv8xy,GFT: Graph Foundation Model with Transferable Tree Vocabulary,Graph Foundation Model;Transferability;Computation Tree;Graph Neural Network,6.0,3.75,Zehong Wang;Zheyuan Zhang;Nitesh V Chawla;Chuxu Zhang;Yanfang Ye,University of Notre Dame;University of Notre Dame;University of Notre Dame;University of Notre Dame,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96932,,,https://openreview.net/forum?id=0MXzbAv8xy,
2,39,0.06407858,0.09707585,0,0.06416460631639377,0.015145813478756244,"[0.99343319765773, 7.624363896369283e-06, 4.5466190406930004e-05, 0.0016701085996000881, 0.0048436031883668336]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0NMzBwqaAJ,Not All Tokens Are What You Need for Pretraining,pre-training;next token prediction;data optimization;data selection,7.666666666666667,4.0,Zhenghao Lin;Zhibin Gou;Yeyun Gong;Xiao Liu;yelong shen;Ruochen Xu;Chen Lin;Yujiu Yang;Jian Jiao;Nan Duan;Weizhu Chen,Xiamen University;Microsoft;Microsoft Research Asia;Microsoft Research;Xiamen University;Tsinghua University;Microsoft;Microsoft Research Asia;Microsoft GenAI,MS student;Intern;Researcher;Researcher;Full Professor;Full Professor;Principal Researcher;Principal Researcher;Vice President,https://neurips.cc/virtual/2024/poster/96931,,,https://openreview.net/forum?id=0NMzBwqaAJ,/media/PosterPDFs/NeurIPS%202024/96931.png?t=1733724962.7310221
2,40,-0.021407472,0.09407413,0,0.06416460631639377,0.015145813478756244,"[0.7929811437384918, 2.0611032350065398e-07, 0.0005149130650320804, 0.0018679576558434455, 0.2046357794303091]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0NQzQVu9tY,DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors,representation learning;offline reinforcement learning;behavioral cloning;visual distractor,7.0,3.0,Joseph Ortiz;Antoine Dedieu;Wolfgang Lehrach;J Swaroop Guntupalli;Carter Wendelken;Ahmad Humayun;Sivaramakrishnan Swaminathan;Guangyao Zhou;Miguel Lazaro-Gredilla;Kevin Patrick Murphy,Google DeepMind;Google DeepMind;Google Deepmind;Google DeepMind;Google;Google DeepMind;Google DeepMind;Google DeepMind;Google Deepmind;Google,Researcher;Researcher;Researcher;Researcher;Researcher;Researcher;Research Engineer;Research Scientist;Research Scientist;Principal Researcher,https://neurips.cc/virtual/2024/poster/97877,,,,/media/PosterPDFs/NeurIPS%202024/97877.png?t=1733266397.4133346
2,41,-0.056248758,0.025906589,0,0.06416460631639377,0.015145813478756244,"[0.568921314565029, 7.329491842778066e-07, 5.142725199460539e-06, 0.012052123197262591, 0.41902068656332464]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0SMhqvgHST,EEVEE and GATE: Finding the right benchmarks and how to run them seamlessly,multi-modal;benchmarks;machine learning;model evaluation;benchmark frameworks,6.0,4.0,Antreas Antoniou;Eleni Triantafillou;Hugo Larochelle;Sebastien Montella;Fady Rezk;Kiyoon Kim;Linus Ericsson;Pavlos Vougiouklis;Justin Engelmann;Elliot J. Crowley;Srihari Humbarwadi;Yi Liu;Guang Yang;Jeff Z. Pan;Amos Storkey,"Google;Google;Huawei Technologies Ltd.;Samsung;Deargen;University of Edinburgh, University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh, University of Edinburgh;University of Edinburgh",Researcher;Research Scientist;Researcher;Intern;Researcher;Postdoc;Researcher;Assistant Professor;Researcher;Full Professor;Full Professor,,,,,
2,42,-0.15132618,0.02146309,4,-0.20935347267655594,-0.000529932480074861,"[0.04137137429488077, 1.7366546883775704e-09, 1.0606269674784266e-05, 0.0016128329833337578, 0.9570051847154561]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0SRJBtTNhX,IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors,Graph Machine Learning;Graph Data Augmentation;Graph Neural Networks,5.5,4.0,Shenghe Zheng;Hongzhi Wang;Xianglong Liu,Harbin Institute of Technology;Harbin Institute of Technology;Harbin Institute of Technology,MS student;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96930,,,https://openreview.net/forum?id=0SRJBtTNhX,/media/PosterPDFs/NeurIPS%202024/96930.png?t=1732617637.3891017
2,43,-0.18518934,0.0027779788,4,-0.20935347267655594,-0.000529932480074861,"[0.01775326998405469, 4.858134721709234e-10, 3.6660320724528196e-06, 0.0014452108978094233, 0.9807978526002499]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0T8xRFrScB,Benchmarking Counterfactual Image Generation,benchmark;causal inference;counterfactual image generation,7.25,3.75,Thomas Melistas;Nikos Spyrou;Nefeli Gkouti;Pedro Sanchez;Athanasios Vlontzos;Yannis Panagakis;Giorgos Papanastasiou;Sotirios A. Tsaftaris,"University of Athens;University of Athens;University of Athens;University of Edinburgh, University of Edinburgh;Spotify;Pfizer;University of Edinburgh",PhD student;PhD student;PhD student;PhD student;Researcher;Principal Researcher;Professor in machine learning and computer vision,https://neurips.cc/virtual/2024/poster/97876,,,,/media/PosterPDFs/NeurIPS%202024/97876.png?t=1731712408.6398222
2,44,0.5118622,-0.024860546,1,0.3965452440744716,-0.08384307613416417,"[1.2883619056222005e-05, 0.9999862999894996, 5.228291849545128e-20, 8.16391444089239e-07, 1.4456554559669337e-21]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0TUMAAb3of,Queueing Matching Bandits with Preference Feedback,Bandits;Queue;Preference Feedback,6.0,2.5,Jung-hun Kim;Min-hwan Oh,Seoul National University;Seoul National University,Assistant Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96929,,,https://openreview.net/forum?id=0TUMAAb3of,/media/PosterPDFs/NeurIPS%202024/96929.png?t=1733803835.532587
2,45,-0.0018669573,0.3644946,2,-0.09636739540443189,0.3320709647221278,"[0.0018532801635514219, 7.046721091672674e-16, 0.9981372152623544, 1.0248975876759554e-10, 9.504471603627644e-06]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,0VeSCjRDBy,Adversarial Moment-Matching Distillation of Large Language Models,Knowledge distillation;Large language models;Imitation learning;Moment-matching;Adversarial training,6.25,3.0,Chen Jia,,,https://neurips.cc/virtual/2024/poster/96928,,,https://openreview.net/forum?id=0VeSCjRDBy,/media/PosterPDFs/NeurIPS%202024/96928.png?t=1731660620.7591212
2,46,-0.24925767,0.015651966,4,-0.20935347267655594,-0.000529932480074861,"[0.0026510730019921823, 3.890094086284624e-12, 2.630701464105872e-05, 0.0002315395321600986, 0.9970910804473165]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0WCFI2Qx85,ScaleKD: Strong Vision Transformers Could Be Excellent Teachers,knowledge distillation;model compression;training acceleration;vision transformer;convolutional neural network;multi-layer perception,6.25,4.5,Jiawei Fan;Chao Li;Xiaolong Liu;Anbang Yao,Intel Labs China;Intel;Intel,Research Intern;Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96927,,,https://openreview.net/forum?id=0WCFI2Qx85,/media/PosterPDFs/NeurIPS%202024/96927.png?t=1731695837.2500114
2,47,0.2804453,-0.1894261,1,0.3965452440744716,-0.08384307613416417,"[0.0029263933209318616, 0.9942464039996853, 1.4864796730699136e-23, 0.00282720267906059, 3.221099389783081e-13]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0XKvW4ijxp,Learning-Augmented Algorithms with Explicit Predictors,online algorithms;learning-augmented algorithms;scheduling;caching,6.0,4.0,Marek Elias;Haim Kaplan;Yishay Mansour;Shay Moran,"Bocconi University;Technion, Technion;School of Computer Science, Tel Aviv University",Assistant Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96926,,,https://openreview.net/forum?id=0XKvW4ijxp,/media/PosterPDFs/NeurIPS%202024/96926.png?t=1733319671.0065775
2,48,0.37225774,-0.11562894,1,0.3965452440744716,-0.08384307613416417,"[0.00046236615862407863, 0.9994038615221841, 1.6974044745880862e-21, 0.00013377231919126282, 6.038899063881451e-16]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0XeNkkENuI,The Road Less Scheduled,Stochastic Optimization;Optimization;Convex Optimization;Learning Rates;Learning Rate Schedules,7.5,3.5,Aaron Defazio;Xingyu Alice Yang;Ahmed Khaled;Konstantin Mishchenko;Harsh Mehta;Ashok Cutkosky,Meta;Meta;Princeton University;Samsung;Google Research;Boston University,Research Scientist;Research Engineer;PhD student;Researcher;Software Engineer;Assistant Professor,https://neurips.cc/virtual/2024/poster/96925,,,https://openreview.net/forum?id=0XeNkkENuI,/media/PosterPDFs/NeurIPS%202024/96925.png?t=1730837481.9895687
2,49,0.1460578,0.21914145,0,0.06416460631639377,0.015145813478756244,"[0.985085371603473, 1.0215494911866756e-06, 0.014853342570741274, 2.162006157914776e-05, 3.86442147154987e-05]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0ZZMUjZJYF,Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study,LLMs;Learning by Teaching;Reasoning;Mathematical Reasoning;Code Synthesis;Weak-to-Strong Generalization;In-Context Learning;Prompting;Knowledge Distillation;Education-Inspired,6.5,4.0,Xuefei Ning;Zifu Wang;Shiyao Li;Zinan Lin;Peiran Yao;Tianyu Fu;Matthew B. Blaschko;Guohao Dai;Huazhong Yang;Yu Wang,Tsinghua University;KU Leuven;Tsinghua University;Microsoft;Infinigence;Shanghai Jiaotong University;Tsinghua University;Tsinghua University;KU Leuven,Research Assistant Professor;PhD student;PhD student;Senior Researcher;Researcher;Associate Professor;Full Professor;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96924,,,https://openreview.net/forum?id=0ZZMUjZJYF,/media/PosterPDFs/NeurIPS%202024/96924.png?t=1732367562.4969194
2,50,0.07159563,-0.024327766,0,0.06416460631639377,0.015145813478756244,"[0.9488885130602378, 0.0012013368471842578, 8.081770633620587e-10, 0.0487869241784102, 0.0011232251059904773]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0ZeONp33f0,Graph Neural Networks and Arithmetic Circuits,Machine Learning;Graph Neural Networks;Arithmetic Circuits;Computational Complexity,6.5,3.25,Timon Barlag;Vivian Holzapfel;Laura Strieker;Jonni Virtema;Heribert Vollmer,Universität Hannover;Leibniz Universität Hannover;Leibniz Universität Hannover;University of Sheffield;Leibniz Universität Hannover,PhD student;Undergrad student;PhD student;Lecturer;Full Professor,https://neurips.cc/virtual/2024/poster/96923,,,https://openreview.net/forum?id=0ZeONp33f0,/media/PosterPDFs/NeurIPS%202024/96923.png?t=1732106485.9402945
2,51,-0.078428976,-0.18954016,3,-0.12954866399913614,-0.26501765285515333,"[0.23902587092477603, 0.0003423975930341381, 7.701408952974434e-16, 0.7554663674227953, 0.005165364059393736]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,0aN7VWwp4g,Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting,Precipitation Nowcasting;Video Prediction;Fourier Analysis;Loss Function,6.0,4.0,Chiu-Wai Yan;Shi Quan Foo;Van-Hoan Trinh;Dit-Yan Yeung;Ka-Hing Wong;Wai-Kin Wong,Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology,Chair Professor;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96922,,,https://openreview.net/forum?id=0aN7VWwp4g,/media/PosterPDFs/NeurIPS%202024/96922.png?t=1731480203.951872
2,52,-0.23586994,0.37846398,2,-0.09636739540443189,0.3320709647221278,"[6.797409537598867e-07, 1.7801769719875983e-24, 0.9999905338073318, 4.1886457279797016e-14, 8.786451672499288e-06]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,0bFXbEMz8e,FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions,generative models;material generation;chemistry;flow matching;large language models,6.0,4.333333333333333,Anuroop Sriram;Benjamin Kurt Miller;Ricky T. Q. Chen;Brandon M Wood,"Meta Facebook;University of Amsterdam;FAIR at Meta;FAIR Labs, Meta AI",Principal Researcher;PhD student;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96921,,,https://openreview.net/forum?id=0bFXbEMz8e,/media/PosterPDFs/NeurIPS%202024/96921.png?t=1730973273.143089
2,53,-0.15925287,-0.015642455,4,-0.20935347267655594,-0.000529932480074861,"[0.04865646193556364, 7.640378269839417e-09, 6.450339768964893e-07, 0.0055776771882226316, 0.9457652082018587]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0bINeW40u4,Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning,Medical Multi-modal Alignment;Eye-gaze;Radiology,6.25,3.5,Chong Ma;Hanqi Jiang;Wenting Chen;Yiwei Li;Zihao Wu;Xiaowei Yu;Zhengliang Liu;Lei Guo;Dajiang Zhu;Tuo Zhang;Dinggang Shen;Tianming Liu;Xiang Li,"Northwest Polytechnical University Xi'an;Beijing Jiaotong University;City University of Hong Kong;University of Georgia;University of Georgia;University of Texas at Arlington, University of Texas at Arlington;University of Georgia;University of Texas at Arlington;Northwestern Polytechnical University;ShanghaiTech University;University of Georgia;Massachusetts General Hospital, Harvard University",PhD student;Undergrad student;PhD student;PhD student;PhD student;PhD student;PhD student;Assistant Professor;Associate Professor;Full Professor;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96920,,,https://openreview.net/forum?id=0bINeW40u4,
2,54,0.38273144,-0.19184409,1,0.3965452440744716,-0.08384307613416417,"[6.544717096956129e-05, 0.9998685461552613, 1.1233835846797795e-26, 6.6006673769135e-05, 4.4508371404536634e-18]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0cSQ1Sg7db,Generalization of Hamiltonian algorithms,Generalization;stochastic algorithms;concentration inequalities;PAC-Bayes,6.5,3.0,Andreas Maurer,,,https://neurips.cc/virtual/2024/poster/96919,,,https://openreview.net/forum?id=0cSQ1Sg7db,
2,55,-0.029614072,-0.05991212,0,0.06416460631639377,0.015145813478756244,"[0.7996023694630796, 8.213878553920841e-05, 7.880140560453479e-10, 0.14110060515838035, 0.059214885804986774]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0cgDDa4OFr,Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation,source distribution estimation;maximum entropy;Sliced-Wasserstein distance;empirical Bayes;simulation-based inference,5.8,2.8,Julius Vetter;Guy Moss;Cornelius Schröder;Richard Gao;Jakob H. Macke,Eberhard-Karls-Universität Tübingen;Eberhard-Karls-Universität Tübingen;University Tübingen;Eberhard-Karls-Universität Tübingen,PhD student;PhD student;Postdoc;Postdoc,https://neurips.cc/virtual/2024/poster/96918,,,https://openreview.net/forum?id=0cgDDa4OFr,/media/PosterPDFs/NeurIPS%202024/96918.png?t=1733318904.6928847
2,56,-0.041920777,-0.1336057,0,0.06416460631639377,0.015145813478756244,"[0.5122276642754375, 0.0004326652383788781, 2.7953801513192786e-13, 0.47476955932040615, 0.012570111165497671]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0d50Il6enG,Non-parametric classification via expand-and-sparsify representation,non-parametric regression;non-parametric classification;expand-and-sparsify representation;universal consistency;minimax-optimal convergence rate,6.0,3.0,Kaushik Sinha,Wichita State University,Associate Professor,https://neurips.cc/virtual/2024/poster/96917,,,https://openreview.net/forum?id=0d50Il6enG,/media/PosterPDFs/NeurIPS%202024/96917.png?t=1731697679.5420048
2,57,-0.05421332,-0.22073112,3,-0.12954866399913614,-0.26501765285515333,"[0.18075675756568302, 0.0014037463991435444, 3.9978302379022894e-18, 0.8173114026463785, 0.0005280933887947568]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,0dtA21q83C,DeNetDM: Debiasing by Network Depth Modulation,Trustworthy Machine Learning;Debiasing;Robustness,6.0,3.5,Silpa Vadakkeeveetil Sreelatha;Adarsh Kappiyath;Abhra Chaudhuri;Anjan Dutta,University of Surrey;University of Exeter;University of Surrey,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96916,,,https://openreview.net/forum?id=0dtA21q83C,/media/PosterPDFs/NeurIPS%202024/96916.png?t=1733689557.490417
2,58,-0.19589648,0.09422963,4,-0.20935347267655594,-0.000529932480074861,"[0.006899674073996519, 1.7067094199767967e-12, 0.003351968275624774, 3.700109062021821e-05, 0.9897113565580518]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0e5uOaJxo1,Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure,Graph Neural Network;Protein Sequence;Structure,5.0,3.3333333333333335,Bozhen Hu;Cheng Tan;Jun Xia;Yue Liu;Lirong Wu;Jiangbin Zheng;Yongjie Xu;Yufei Huang;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University, China;National University of Singapore;Westlake University;Westlake University;Westlake University;Zhejiang University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96915,,,https://openreview.net/forum?id=0e5uOaJxo1,/media/PosterPDFs/NeurIPS%202024/96915.png?t=1730385968.8958924
2,59,0.09615892,0.18102637,0,0.06416460631639377,0.015145813478756244,"[0.9929936406786175, 6.763285843200197e-07, 0.006116087807998768, 9.238123386621338e-05, 0.0007972139509333788]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0feJEykDRx,Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models,spatial-temporal data mining;location-based service;check-in sequence;large language model,5.75,4.0,Letian Gong;Yan Lin;Xinyue Zhang;Yiwen Lu;Xuedi Han;Yichen Liu;Shengnan Guo;Youfang Lin;Huaiyu Wan,Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University,PhD student;PhD student;Undergrad student;Undergrad student;MS student;Associate Professor;Full Professor;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96914,,,https://openreview.net/forum?id=0feJEykDRx,/media/PosterPDFs/NeurIPS%202024/96914.png?t=1731289337.5941467
2,60,-0.013711061,-0.07216554,0,0.06416460631639377,0.015145813478756244,"[0.8008296575141028, 0.00022837786823016518, 1.2050336869269433e-10, 0.17532906257682887, 0.02361290192033479]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0jld45XGgJ,Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?,neural collapse;deep neural collapse;unconstrained features model;deep unconstrained features model;low-rank bias,6.5,3.75,Peter Súkeník;Christoph H. Lampert;Marco Mondelli,Institute of Science and Technology;Institute of Science and Technology Austria;Institute of Science and Technology Austria,PhD student;Assistant Professor;Professor,https://neurips.cc/virtual/2024/poster/96913,,,https://openreview.net/forum?id=0jld45XGgJ,
2,61,0.49365819,-0.019841706,1,0.3965452440744716,-0.08384307613416417,"[3.182421090892695e-05, 0.9999664886350949, 3.2376008237137405e-19, 1.687153996441425e-06, 1.8041994488616e-20]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0l9yGPTHAU,Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms,Robust Markov decision process;norm;sample complexity;strong duality,6.5,3.0,Pierre Clavier;Laixi Shi;Erwan Le Pennec;Eric Mazumdar;Adam Wierman;Matthieu Geist,"École Polytechnique;California Institute of Technology;Ecole polytechnique;Deparment of Computing + Mathematical Sciences, California Institute of Technology;California Institute of Technology;Google",PhD student;Postdoc;Full Professor;Assistant Professor;Professor;Researcher,https://neurips.cc/virtual/2024/poster/96912,,,https://openreview.net/forum?id=0l9yGPTHAU,
2,62,-0.096782275,0.2680031,2,-0.09636739540443189,0.3320709647221278,"[0.003340358677108283, 4.658524128927784e-15, 0.9909285534367959, 1.675967007881117e-08, 0.005731071126421099]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,0lBx844upd,ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models,network pruning;unstructured pruning;large language model;ADMM;pre-conditioned conjugate gradient;optimization,5.333333333333333,3.0,Xiang Meng;Kayhan Behdin;Haoyue Wang;Rahul Mazumder,Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology,PhD student;PhD student;PhD student;Associate Professor,https://neurips.cc/virtual/2024/poster/96911,,,https://openreview.net/forum?id=0lBx844upd,/media/PosterPDFs/NeurIPS%202024/96911.png?t=1731079283.0533488
2,63,-0.07022652,-0.30347943,3,-0.12954866399913614,-0.26501765285515333,"[0.0643205452621255, 0.0025279886583942407, 3.636479432324831e-23, 0.933137174114072, 1.429196540816873e-05]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,0lau89u4oE,Accelerating Non-Maximum Suppression: A Graph Theory Perspective,non-maximum suppression;object detection;graph theory,5.5,3.25,King-Siong Si;Lu Sun;Weizhan Zhang;Tieliang Gong;Jiahao Wang;Jiang Liu;Hao Sun,Xi'an Jiaotong University;Xi'an Jiaotong University;North China University of Technology;China Telecom Corporation Ltd. Data&AI Technology Company,MS student;MS student;MS student;Researcher,https://neurips.cc/virtual/2024/poster/96910,,,https://openreview.net/forum?id=0lau89u4oE,/media/PosterPDFs/NeurIPS%202024/96910.png?t=1733315333.5240822
2,64,-0.08510746,-0.26066056,3,-0.12954866399913614,-0.26501765285515333,"[0.09434876115033938, 0.0008156578291874756, 4.071932521281832e-20, 0.9046184191485196, 0.00021716187195360635]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,0m19blQT6y,BitsFusion: 1.99 bits Weight Quantization of Diffusion Model,Diffusion;Quantization;Stable Diffusion;Low bit,5.75,4.5,Yang Sui;Yanyu Li;Anil Kag;Yerlan Idelbayev;Junli Cao;Ju Hu;Dhritiman Sagar;Bo Yuan;Sergey Tulyakov;Jian Ren,Rutgers University;Northeastern University;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Rutgers University;Snap Inc.;Snap Inc.,PhD student;PhD student;Researcher;Researcher;Researcher;Researcher;Researcher;Assistant Professor;Director of Research;Research Scientist,https://neurips.cc/virtual/2024/poster/96909,,,https://openreview.net/forum?id=0m19blQT6y,/media/PosterPDFs/NeurIPS%202024/96909.png?t=1729915675.3170154
2,65,-0.00251228,0.3769304,2,-0.09636739540443189,0.3320709647221278,"[0.0012766817980408146, 2.2073869424585598e-16, 0.9987184307282594, 3.9472003587454695e-11, 4.887434227409756e-06]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,0mRouJElbZ,ProgressGym: Alignment with a Millennium of Moral Progress,Progress Alignment;AI Alignment;Large Language Models,7.666666666666667,2.6666666666666665,Tianyi Qiu;Yang Zhang;Xuchuan Huang;Jasmine Xinze Li;Jiaming Ji;Yaodong Yang,"University of California, Berkeley;Peking University;Peking University;Peking University;Peking University;Peking University",Intern;Undergrad student;Undergrad student;Intern;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/97875,,,,/media/PosterPDFs/NeurIPS%202024/97875.png?t=1731742041.9348912
2,66,0.42614552,0.08994585,1,0.3965452440744716,-0.08384307613416417,"[0.015087584320665195, 0.9848754631200393, 2.4741552970948614e-11, 3.69525345482582e-05, 5.710993845161551e-15]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0nSY8NiILP,Tight Bounds for Learning RUMs from Small Slates,discrete choice;random utility model;approximation theory,6.0,2.75,Flavio Chierichetti;Mirko Giacchini;Ravi Kumar;Alessandro Panconesi;Andrew Tomkins,Sapienza University of Rome;Sapienza University of Rome;Google;Sapienza University of Rome;Google,Full Professor;PhD student;Research Scientist;Full Professor;Researcher,https://neurips.cc/virtual/2024/poster/96908,,,https://openreview.net/forum?id=0nSY8NiILP,/media/PosterPDFs/NeurIPS%202024/96908.png?t=1732698791.0319488
2,67,0.25132486,-0.20319358,1,0.3965452440744716,-0.08384307613416417,"[0.006206021759759015, 0.9862660553468395, 1.3083594853585837e-23, 0.007527922890399047, 3.002424290390839e-12]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0nzKznCjFG,Private and Personalized Frequency Estimation in a Federated Setting,federated learning;personalization;privacy,5.75,3.0,Amrith Setlur;Vitaly Feldman;Kunal Talwar,Carnegie Mellon University;Apple AI Research;Apple,PhD student;Research Scientist;Research Scientist,https://neurips.cc/virtual/2024/poster/96907,,,https://openreview.net/forum?id=0nzKznCjFG,
2,68,-0.18157998,0.03947093,4,-0.20935347267655594,-0.000529932480074861,"[0.013917101324751149, 8.278108194640658e-11, 5.572558892459954e-05, 0.00038295059319044805, 0.9856442224103529]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0o7Rd5jngV,Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling,Transformer;expressive power;theoretical insights,6.333333333333333,3.0,Mingze Wang;Weinan E,Peking University;Peking University,PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96906,,,https://openreview.net/forum?id=0o7Rd5jngV,
2,69,-0.12251995,-0.049827244,4,-0.20935347267655594,-0.000529932480074861,"[0.2201930630522636, 5.308293046432494e-07, 2.4544138823207938e-08, 0.048984569445015065, 0.7308218121292779]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0o9E8AsFgW,DarkSAM: Fooling Segment Anything Model to Segment Nothing,Segment Anything Model;Adversarial Example,6.333333333333333,4.0,Ziqi Zhou;Yufei Song;Minghui Li;Shengshan Hu;Xianlong Wang;Leo Yu Zhang;Dezhong Yao;Hai Jin,Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Griffith University;Huazhong University of Science and Technology;Huazhong University of Science and Technology,PhD student;PhD student;Assistant Professor;Associate Professor;PhD student;Researcher;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96905,,,https://openreview.net/forum?id=0o9E8AsFgW,
2,70,-0.18423451,0.25213403,2,-0.09636739540443189,0.3320709647221278,"[0.0003076625815189531, 2.3289616489822097e-17, 0.9872567112328301, 4.337738327078117e-09, 0.012435621847912444]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,0oUutV92YF,ProtGO: Function-Guided Protein Modeling for Unified Representation Learning,Teacher-student;Knowledge Distillation;Protein Function,5.666666666666667,3.6666666666666665,Bozhen Hu;Cheng Tan;Yongjie Xu;Zhangyang Gao;Jun Xia;Lirong Wu;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University;Westlake University, China;Westlake University, China;Westlake University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96904,,,https://openreview.net/forum?id=0oUutV92YF,/media/PosterPDFs/NeurIPS%202024/96904.png?t=1730386167.5899446
2,71,-0.04843812,0.4040603,2,-0.09636739540443189,0.3320709647221278,"[0.00017374832256483985, 5.949192875775509e-19, 0.9998240632325298, 1.5862555975861462e-12, 2.188443319026816e-06]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,0og7nmvDbe,Confidence Regulation Neurons in Language Models,LLMs;Interpretability;Mechanistic Interpretability,7.0,3.75,Alessandro Stolfo;Ben Peng Wu;Wes Gurnee;Yonatan Belinkov;Xingyi Song;Mrinmaya Sachan;Neel Nanda,"ETHZ - ETH Zurich;University of Sheffield;Massachusetts Institute of Technology;Technion, Technion;University of Sheffield;Google DeepMind;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Assistant Professor;Lecturer;Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96903,,,https://openreview.net/forum?id=0og7nmvDbe,
2,72,0.25011468,-0.18353273,1,0.3965452440744716,-0.08384307613416417,"[0.009825207243066757, 0.9812594492230995, 2.838444659948694e-22, 0.008915343524120396, 9.713295288684171e-12]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0qb8KoPsej,Accelerating Matroid Optimization through Fast Imprecise Oracles,matroid optimization;weak-strong models;learning-augmented algorithms;algorithms with predictions;query minimization;robustness,5.5,2.75,Franziska Eberle;Felix Hommelsheim;Alexander Lindermayr;Zhenwei Liu;Nicole Megow;Jens Schlöter,Technische Universität Berlin;Universität Bremen;Universität Bremen;Universität Bremen;Universität Bremen,Postdoc;Postdoc;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96902,,,https://openreview.net/forum?id=0qb8KoPsej,
2,73,0.24778247,-0.18444899,1,0.3965452440744716,-0.08384307613416417,"[0.010460308141147732, 0.9798889614482025, 2.8949602235924943e-22, 0.009650730398959192, 1.1690815746667423e-11]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0rl5vWOzRU,Score-Optimal Diffusion Schedules,Diffusion model;adaptive schedule;Annealed Langevin,6.0,3.0,Christopher Williams;Andrew Campbell;Arnaud Doucet;Saifuddin Syed,University of Oxford;University of Oxford;University of Oxford;University of Oxford,PhD student;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96901,,,https://openreview.net/forum?id=0rl5vWOzRU,
2,74,-0.17648138,-0.41862112,3,-0.12954866399913614,-0.26501765285515333,"[0.012261012640773722, 0.0002964697415582891, 2.8462893531199104e-29, 0.9874420893464368, 4.282712311571878e-07]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,0sJBW05a2W,3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration,Point Cloud Registration;Focus and Matching,5.666666666666667,4.333333333333333,Liyuan Zhang;Le Hui;qi liu;Bo Li;Yuchao Dai,Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwestern Polytechnical University Xi'an;Northwestern Polytechnical University,MS student;Associate Professor;Researcher;Associate Professor;Professor,https://neurips.cc/virtual/2024/poster/96900,,,https://openreview.net/forum?id=0sJBW05a2W,/media/PosterPDFs/NeurIPS%202024/96900.png?t=1731333373.8074756
2,75,-0.16704087,-0.3598848,3,-0.12954866399913614,-0.26501765285515333,"[0.019480196623884057, 0.00017581371774313896, 2.6660621897620874e-25, 0.9803334197536517, 1.0569904721184197e-05]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,0sycTGl4In,4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization,Dynamic Novel View Synthesis;4D Gaussian splatting;Sparse reconstruction;in-the-wild,5.333333333333333,4.666666666666667,Mijeong Kim;Jongwoo Lim;Bohyung Han,Seoul National University;Seoul National University,Full Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96899,,,https://openreview.net/forum?id=0sycTGl4In,/media/PosterPDFs/NeurIPS%202024/96899.png?t=1733712090.5881364
2,76,0.61073065,0.018717432,1,0.3965452440744716,-0.08384307613416417,"[4.847899082014725e-07, 0.9999994978503578, 2.9994589517608565e-20, 1.7359734121666263e-08, 1.405175572022703e-26]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,0uGlKYS7a2,Maximizing utility in multi-agent environments by anticipating the behavior of other learners,Game Theory; no regret; learning theory;,5.5,3.25,Angelos Assos;Yuval Dagan;Constantinos Costis Daskalakis,Massachusetts Institute of Technology;Massachusetts Institute of Technology,MS student;Full Professor,https://neurips.cc/virtual/2024/poster/96898,,,https://openreview.net/forum?id=0uGlKYS7a2,/media/PosterPDFs/NeurIPS%202024/96898.png?t=1731753379.9098587
2,77,-0.07488669,0.3827278,2,-0.09636739540443189,0.3320709647221278,"[0.00012937915225438528, 4.834475137336001e-19, 0.9998621582074517, 3.529108228735172e-12, 8.462636764674075e-06]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,0uXtFk5KNJ,BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models,block coordinate descent;large language models,5.25,3.75,Qijun Luo;Hengxu Yu;Xiao Li,"The Chinese University of Hong Kong, Shenzhen;The Chinese University of Hong Kong, Shenzhen;Chinese University of Hong Kong Shen Zhen",PhD student;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96897,,,https://openreview.net/forum?id=0uXtFk5KNJ,/media/PosterPDFs/NeurIPS%202024/96897.png?t=1733743857.9232197
2,78,0.022653038,0.24370801,2,-0.09636739540443189,0.3320709647221278,"[0.33050553194075294, 3.6886392119419516e-10, 0.6639816464644208, 3.2129715717935003e-06, 0.00550960825439054]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,0zFVhMBZHJ,Mixture of Tokens: Continuous MoE through Cross-Example Aggregation,LLM;Mixture of Experts;MoE;conditional computation;fully-differentiable;language modeling,6.0,3.6666666666666665,Szymon Antoniak;Michał Krutul;Maciej Pióro;Jakub Krajewski;Jan Ludziejewski;Kamil Ciebiera;Krystian Król;Tomasz Odrzygóźdź;Marek Cygan;Sebastian Jaszczur,IDEAS NCBR Sp.;IDEAS NCBR Sp.;University of Warsaw;University of Warsaw;IDEAS NCBR Sp.;University of Warsaw;IDEAS NCBR;Nomagic;University of Warsaw,PhD student;Researcher;PhD student;PhD student;Intern;MS student;Postdoc;Founder / CTO;PhD student,https://neurips.cc/virtual/2024/poster/96896,,,https://openreview.net/forum?id=0zFVhMBZHJ,/media/PosterPDFs/NeurIPS%202024/96896.png?t=1730308223.324062
2,79,0.24368975,0.18879418,0,0.06416460631639377,0.015145813478756244,"[0.999381797952803, 0.0003629971239658803, 0.0001860632230178966, 6.899841371905057e-05, 1.43286494042613e-07]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,0zWzJj6lO3,Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents,cooperative AI;AI safety;LLM agents;cognitive science;language model evaluation;dynamic evaluation;alignment;agency;evolving benchmarks;multi-agent interactions,5.75,3.5,Giorgio Piatti;Zhijing Jin;Max Kleiman-Weiner;Bernhard Schölkopf;Mrinmaya Sachan;Rada Mihalcea,Common Sense Machines;University of Michigan;Swiss Federal Institute of Technology,Principal Researcher;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96895,,,https://openreview.net/forum?id=0zWzJj6lO3,
2,80,-0.16938657,-0.05973538,4,-0.20935347267655594,-0.000529932480074861,"[0.06772955973929795, 4.5755344356183554e-08, 2.0518523442784197e-08, 0.025648254324839567, 0.9066221196619946]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,0zfUiSX5si,AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases,De Novo Peptide sequencing;Proteomics;Mass Spectrum,5.333333333333333,3.0,Jun Xia;Shaorong Chen;Jingbo Zhou;Xiaojun Shan;Wenjie Du;Zhangyang Gao;Cheng Tan;Bozhen Hu;Jiangbin Zheng;Stan Z. Li,"Westlake University, China;Westlake University;Jilin University;University of Electronic Science and Technology of China;University of Science and Technology of China;Westlake University, China;Zhejiang University & Westlake University;Westlake University;Westlake University;Westlake University",PhD student;PhD student;Undergrad student;Undergrad student;Assistant Professor;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96894,,,https://openreview.net/forum?id=0zfUiSX5si,
2,81,-0.25151917,-0.28693447,3,-0.12954866399913614,-0.26501765285515333,"[0.020056221967176772, 2.5930383169330026e-06, 6.682612846881701e-19, 0.9766210665006138, 0.003320118493892435]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,105ZuvpdyW,SegVol: Universal and Interactive Volumetric Medical Image Segmentation,Volumetric Medical Image Segmentation;3D Segmentation Foundation Model;Universal and Interactive 3D Segmentation,7.666666666666667,4.333333333333333,Yuxin Du;Fan BAI;Tiejun Huang;Bo Zhao,Beijing Academy of Artificial Intelligence;The Chinese University of Hong Kong;Peking University;BAAI,Intern;PhD student;Full Professor;Principal Researcher,https://neurips.cc/virtual/2024/poster/96893,,,https://openreview.net/forum?id=105ZuvpdyW,/media/PosterPDFs/NeurIPS%202024/96893.png?t=1731410503.871179
2,82,0.04577409,-0.24324691,3,-0.12954866399913614,-0.26501765285515333,"[0.19619196345823664, 0.0691680845756178, 3.473265991590308e-21, 0.7346371002186562, 2.851747489215527e-06]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,1067784F6e,Data Distribution Valuation,Data distribution valuation;Huber model;Maximum mean discrepancy,6.333333333333333,4.333333333333333,Xinyi Xu;Shuaiqi Wang;Chuan-Sheng Foo;Bryan Kian Hsiang Low;Giulia Fanti,"National University of Singapore;Carnegie Mellon University;Institute for Infocomm Research, A*STAR;National University of Singapore;Carnegie Mellon University",PhD student;PhD student;Principal Scientist;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96892,,,https://openreview.net/forum?id=1067784F6e,/media/PosterPDFs/NeurIPS%202024/96892.png?t=1731176029.7581189
2,83,-0.22563006,-0.049784996,4,-0.20935347267655594,-0.000529932480074861,"[0.011811554317769911, 7.371541442821568e-10, 1.1141458320579569e-07, 0.005146391611164084, 0.9830419419193285]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,12A1RT1L87,Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?,Dataset Condensation;Dataset Distillation,5.666666666666667,3.6666666666666665,Lingao Xiao;Yang He,"School of Computer Science and  Engineering, Nanyang Technological University;Institute of High Performance Computing, Singapore, A*STAR",Undergrad student;Researcher,https://neurips.cc/virtual/2024/poster/96891,,,https://openreview.net/forum?id=12A1RT1L87,/media/PosterPDFs/NeurIPS%202024/96891.png?t=1731138766.8349779
2,84,-0.20074943,0.040258985,4,-0.20935347267655594,-0.000529932480074861,"[0.007866963829250593, 2.1942113301917523e-11, 7.461139108550749e-05, 0.00023839269567265469, 0.9918200320620493]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,135eKqDoRR,Bayesian-guided Label Mapping for Visual Reprogramming,visual reprogramming;adversarial reprogramming;output label mapping;Bayesian probability,7.25,4.0,Chengyi Cai;Zesheng Ye;Lei Feng;Jianzhong Qi;Feng Liu,University of Melbourne;Singapore University of Technology and Design;University of Melbourne;University of Melbourne,PhD student;Assistant Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96890,,,https://openreview.net/forum?id=135eKqDoRR,
2,85,-0.1496939,0.30529067,2,-0.09636739540443189,0.3320709647221278,"[0.00012199027293279541, 1.760146138045214e-18, 0.9991874536077521, 1.5110291801315596e-10, 0.0006905559682120711]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,14hLJr6kZ3,Enhancing Domain Adaptation through Prompt Gradient Alignment,transfer learning; domain adaptation; prompt-tuning,6.25,3.25,Hoang Phan;Tung Lam Tran;Quyen Tran;Trung Le,VinAi Research;VinAI Research;Monash University;New York University,Research resident;Research Resident;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96889,,,https://openreview.net/forum?id=14hLJr6kZ3,/media/PosterPDFs/NeurIPS%202024/96889.png?t=1732036918.0147438
2,86,0.2630342,0.051892787,0,0.06416460631639377,0.015145813478756244,"[0.8342360898759776, 0.16121630049753738, 2.445866515295105e-09, 0.004547573993119882, 3.31874985716226e-08]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,15460JjocO,Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners,multi-agent;reinforcement learning;robustness;diversity;specialization,7.0,3.6666666666666665,Rujikorn Charakorn;Poramate Manoonpong;Nat Dilokthanakul,Sakana AI;Vidyasirimedhi Institute of Science and Technology;King Mongkut's Institute of Technology Ladkrabang,Intern;Full Professor;Lecturer,https://neurips.cc/virtual/2024/poster/96888,,,https://openreview.net/forum?id=15460JjocO,/media/PosterPDFs/NeurIPS%202024/96888.png?t=1731395258.7214391
2,87,0.61719507,-0.024593957,1,0.3965452440744716,-0.08384307613416417,"[1.3422225514093857e-07, 0.9999998522727689, 7.522759755265688e-23, 1.3504975864208768e-08, 1.192437124008087e-27]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,15Jm9v7wCo,No-Regret Learning for Fair Multi-Agent Social Welfare Optimization,Online Learning;Nash Social Welfare,5.666666666666667,3.3333333333333335,Mengxiao Zhang;Ramiro Deo-Campo Vuong;Haipeng Luo,University of Southern California;University of Southern California,Undergrad student;Associate Professor,https://neurips.cc/virtual/2024/poster/96887,,,https://openreview.net/forum?id=15Jm9v7wCo,
2,88,-0.14552048,-0.15470643,3,-0.12954866399913614,-0.26501765285515333,"[0.2342400069202141, 1.2100028303047813e-05, 9.138390373293144e-13, 0.602985463998266, 0.1627624290523031]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,15PS30UOUp,Kuro Siwo: 33 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping,Synthetic Aperture Radar;SAR;Deep Learning;Remote Sensing;Floods;dataset,6.75,3.75,Nikolaos Ioannis Bountos;Maria Sdraka;Angelos Zavras;Andreas Karavias;Ilektra Karasante;Themistocles Herekakis;Angeliki Thanasou;Dimitrios Michail;Ioannis Papoutsis,National Observatory of Athens;National Observatory of Athens;Harokopio University;The Centre for Research & Technology;National Observatory of Athens ;National Observatoty of Athens;National Observatory of Athens;Harokopio University;National Technical University of Athens,PhD student;Researcher;PhD student;Researcher;Researcher;Researcher;Researcher;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97874,,,,
2,89,0.004352061,-0.07103703,0,0.06416460631639377,0.015145813478756244,"[0.8251880898457892, 0.0004375035486956427, 7.021443278812945e-11, 0.16327804072581295, 0.011096365809487656]","[0.012904257588068188, 0.01712706838507262]",0.20860695137736496,164QnJsYjF,Dense Associative Memory Through the Lens of Random Features,Associative Memory;Kernels;Random Features;Hopfield Network,6.0,3.0,Benjamin Hoover;Duen Horng Chau;Hendrik Strobelt;Parikshit Ram;Dmitry Krotov,International Business Machines;International Business Machines;International Business Machines;Massachusetts Institute of Technology;Georgia Institute of Technology,AI Research Engineer;Principal Researcher;Principal Researcher;Researcher;Full Professor,https://neurips.cc/virtual/2024/poster/96886,,,https://openreview.net/forum?id=164QnJsYjF,/media/PosterPDFs/NeurIPS%202024/96886.png?t=1733846086.053208
2,90,-0.31772932,0.41427824,2,-0.09636739540443189,0.3320709647221278,"[1.7470968575627154e-08, 8.734755702355675e-29, 0.9999994757277413, 2.8311013222115833e-16, 5.068012896175822e-07]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,168NLzTpw8,Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation,Vision-Language;Region-Level Understanding;Multimodal Large Language Model,5.75,3.75,Yaoyuan Liang;Zhuojun Cai;Jian Xu;Guanbo Huang;Yiran Wang;Xiao Liang;Jiahao Liu;Ziran Li;Jingang Wang;Shao-Lun Huang,"Tsinghua Shenzhen International Graduate School, Tsinghua University;Microsoft;University of Electronic Science and Technology of China;Tsinghua University;Tsinghua University;Meituan;Meituan;Tsinghua University",PhD student;Intern;Undergrad student;MS student;MS student;Researcher;Researcher;Associate Professor,https://neurips.cc/virtual/2024/poster/96885,,,https://openreview.net/forum?id=168NLzTpw8,
2,91,-0.118134014,0.26676714,2,-0.09636739540443189,0.3320709647221278,"[0.001703790301349646, 9.89401569968591e-16, 0.9918601045544365, 9.748856786248838e-09, 0.006436095395356106]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,181llen2gw,A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks,Vision-Language Model;Fairness;Debias,6.333333333333333,3.6666666666666665,Hoin Jung;Taeuk Jang;Xiaoqian Wang,Purdue University;Purdue University;Purdue University,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96884,,,https://openreview.net/forum?id=181llen2gw,/media/PosterPDFs/NeurIPS%202024/96884.png?t=1731379505.2628894
2,92,-0.19037005,0.30377576,2,-0.09636739540443189,0.3320709647221278,"[3.065013290433098e-05, 7.871875042315794e-20, 0.9993372375838827, 4.862217659024027e-11, 0.000632112234590914]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,18FGRNd0wZ,Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation,tokenization of crystals;language models;materials generation,6.0,3.5,Keqiang Yan;Xiner Li;Hongyi Ling;Kenna Ashen;Carl Edwards;Raymundo Arroyave;Marinka Zitnik;Heng Ji;Xiaofeng Qian;Xiaoning Qian;Shuiwang Ji,"Texas A&M University;Texas A&M University - College Station;Texas A&M University - College Station;Texas A&M University - College Station;Genentech;Texas A&M University Main Campus;Harvard University;University of Illinois, Urbana-Champaign;Texas A&M University;Texas A&M;Texas A&M University",PhD student;PhD student;PhD student;PhD student;Intern;Assistant Professor;Full Professor;Associate Professor;Full Professor;Professor,https://neurips.cc/virtual/2024/poster/96883,,,https://openreview.net/forum?id=18FGRNd0wZ,/media/PosterPDFs/NeurIPS%202024/96883.png?t=1733428872.6393995
2,93,-0.18803668,0.09546091,4,-0.20935347267655594,-0.000529932480074861,"[0.00866944587688491, 2.7410284330945156e-12, 0.00334798566665877, 4.2597923654250034e-05, 0.9879399705300611]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,18RdkSv9h9,FINALLY: fast and universal speech enhancement with studio-like quality,speech enhancement; generative models,6.5,4.75,Nicholas Babaev;Kirill Tamogashev;Azat Saginbaev;Ivan Shchekotov;Hanbin Bae;Hosang Sung;WonJun Lee;Hoon-Young Cho;Pavel Andreev,"Samsung;Skolkovo Institute of Science and Technology;Moscow Institute of Physics and Technology;Samsung;Samsung;Samsung;Higher School of Economics, Higher School of Economics",Researcher;MS student;MS student;Principal Researcher;Researcher;Vice President;MS student,https://neurips.cc/virtual/2024/poster/96882,,,https://openreview.net/forum?id=18RdkSv9h9,/media/PosterPDFs/NeurIPS%202024/96882.png?t=1731683595.700073
2,94,0.32727078,-0.11709024,1,0.3965452440744716,-0.08384307613416417,"[0.0025610760670852512, 0.9967036399763073, 2.759180036895346e-20, 0.0007352839565222036, 8.539820015591335e-14]","[0.01765043800968463, 0.012313801858227605]",0.1920289039113429,1ATLLgvURu,Learning-Augmented Priority Queues,learning-augmented algorithms;algorithms with predictions;priority queue;shortest paths;Dijkstra,5.75,4.25,Ziyad Benomar;Christian Coester,University of Oxford,Associate Professor,https://neurips.cc/virtual/2024/poster/96881,,,https://openreview.net/forum?id=1ATLLgvURu,
2,95,0.3095995,0.5030761,2,-0.09636739540443189,0.3320709647221278,"[0.09508496329521089, 7.21906884060091e-11, 0.9049150366246552, 7.813969174556056e-12, 1.2915726860325982e-13]","[0.01796571502691698, 0.0053231441004923325]",0.1872390794362503,1BZKqZphsW,Risk-Averse Fine-tuning of Large Language Models,Risk Averse Reinforcement Learning;Large Language Model Finetuning,5.8,3.2,Sapana Chaudhary;Ujwal Dinesha;Dileep Kalathil;Srinivas Shakkottai,Texas A&M University;Texas A&M University - College Station;Texas A&M University;Texas A&M,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96880,,,https://openreview.net/forum?id=1BZKqZphsW,/media/PosterPDFs/NeurIPS%202024/96880.png?t=1733328781.5713553
2,96,-0.26364937,-0.38828564,3,-0.12954866399913614,-0.26501765285515333,"[0.00664689929186086, 8.894910824786031e-06, 1.6957393791983863e-25, 0.9933307065577066, 1.3499239607681594e-05]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,1CssOqRYyz,Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds,compression;point cloud;diffusion,4.0,4.0,Kai Liu;Kang You;Pan Gao,"Nanjing University of Aeronautics and Astronautics;Nanjing university;Nanjing University of Aeronautics and Astronautics, Tsinghua University",MS student;PhD student;Associate Professor,,,,,
2,97,-0.25224024,-0.31188005,3,-0.12954866399913614,-0.26501765285515333,"[0.014894880659644068, 3.829949525782644e-06, 1.6187155405914848e-20, 0.9842315912254066, 0.0008696981654235526]","[0.014253825563804952, 0.009739711369101263]",0.18532994738361072,1Du3mMP5YN,Learning to Shape In-distribution Feature Space for Out-of-distribution Detection,Out-of-distribution Detection,5.75,4.0,Yonggang Zhang;Jie Lu;Bo Peng;Zhen Fang;Yiu-ming Cheung,Hong Kong Baptist University;University of Technology Sydney;University of Technology Sydney,Postdoc;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96879,,,https://openreview.net/forum?id=1Du3mMP5YN,/media/PosterPDFs/NeurIPS%202024/96879.png?t=1731745181.7993424
2,98,-0.30068702,-0.14781809,4,-0.20935347267655594,-0.000529932480074861,"[0.014621797394065885, 3.927280645239552e-09, 1.7579209987885298e-10, 0.11067232519055942, 0.874705873312302]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,1ELFGSNBGC,Multiview Scene Graph,scene representation; spatial understanding; place recognition; object correspondence; scene graph,5.25,3.25,Juexiao Zhang;Gao Zhu;Sihang Li;Xinhao Liu;Haorui Song;Xinran Tang;Chen Feng,New York University;New York University;New York University;New York University;New York University;New York University;New York University,PhD student;MS student;PhD student;PhD student;MS student;MS student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96878,,,https://openreview.net/forum?id=1ELFGSNBGC,/media/PosterPDFs/NeurIPS%202024/96878.png?t=1731728482.5838113
2,99,-0.09486352,0.005280091,4,-0.20935347267655594,-0.000529932480074861,"[0.2691402598375237, 1.8975890298422421e-07, 1.7449902140737002e-06, 0.012190525935401264, 0.7186672794779578]","[0.005806676354195702, 0.005901518148298464]",0.22679511789143106,1F32iCJFfa,Schrodinger Bridge Flow for Unpaired Data Translation,unpaired data translation;diffusion models;Schrodinger bridge;bridge matching;stochastic interpolant;flow matching,6.5,4.0,Valentin De Bortoli;Iryna Korshunova;Andriy Mnih;Arnaud Doucet,University of Oxford;Google DeepMind;Google DeepMind;University of Oxford,Postdoc;Researcher;Research Scientist;Full Professor,https://neurips.cc/virtual/2024/poster/96877,,,https://openreview.net/forum?id=1F32iCJFfa,/media/PosterPDFs/NeurIPS%202024/96877.png?t=1731688420.732189
3,0,0.08799766,-0.06060414,0,0.06424707811349922,-0.010531989839880426,"[0.9715484284144559, 0.0026013331176117636, 1.0443785654313281e-11, 0.025587585144336025, 0.0002626533131524598]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,00Sx577BT3,The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning,numerical simulations;fluid-dynamics;partial differential equations;operator learning,6.666666666666667,3.6666666666666665,Ruben Ohana;Michael McCabe;Lucas Thibaut Meyer;Rudy Morel;Fruzsina Julia Agocs;Miguel Beneitez;Marsha Berger;Blakesley Burkhart;Stuart B. Dalziel;Drummond Buschman Fielding;Daniel Fortunato;Jared A. Goldberg;Keiya Hirashima;Yan-Fei Jiang;Rich Kerswell;Suryanarayana Maddu;Jonah M. Miller;Payel Mukhopadhyay;Stefan S. Nixon;Jeff Shen;Romain Watteaux;Bruno Régaldo-Saint Blancard;François Rozet;Liam Holden Parker;Miles Cranmer;Shirley Ho,"Flatiron Institute;University of Colorado, Boulder;INRIA;Flatiron Institute;Flatiron Institute;University of Cambridge;Flatiron Institute;Rutgers University;University of Cambridge;Simons Foundation;Flatiron Institute;Flatiron Institute;Simons Foundation;University of Cambridge;Flatiron Institute/Simons Foundation;Los Alamos National Laboratory;University of California, Berkeley;University of Cambridge;Princeton University;CEA;Flatiron Institute;Flatiron Institute;Flatiron Institute;University of Cambridge;Carnegie Mellon University;The University of Tokyo",Postdoc;PhD student;PhD student;Postdoc;Postdoc;Postdoc;Full Professor;Assistant Professor;Director of the GK Batchelor Laboratory;Postdoc;Researcher;Postdoc;Researcher;Full Professor;Postdoc;Researcher;Postdoc;PhD student;PhD student;Researcher;Postdoc;Intern;Researcher;Assistant Professor;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/97882,,,,
3,1,-0.08406016,0.2851326,2,-0.09756174176246091,0.3315038065244718,"[0.004548623868420178, 4.500829247165493e-17, 0.9940544407231345, 1.0791113418313145e-08, 0.0013969246173316818]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,00uVk06eVK,On the Noise Robustness of In-Context Learning for Text Generation,In-Context Learning;Large Language Models;Noise Robustness,6.333333333333333,3.0,Hongfu Gao;Feipeng Zhang;Wenyu Jiang;Jun Shu;Feng Zheng;Hongxin Wei,Xi'an Jiaotong University;Xi'an Jiaotong University;Nanjing University;Xi'an Jiaotong University;Southern University of Science and Technology;Southern University of Science and Technology,MS student;Full Professor;PhD student;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96962,,,https://openreview.net/forum?id=00uVk06eVK,/media/PosterPDFs/NeurIPS%202024/96962.png?t=1731587881.4159098
3,2,-0.16364236,-0.11411294,4,-0.20782917179182095,0.0014387222347446277,"[0.16522406900917866, 1.1784046454188168e-07, 1.8091533019848577e-10, 0.2650957729321526, 0.5696800400372888]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,01I55gys19,Few-Class Arena: A Benchmark for Efficient Vision Model Selection and Dataset Difficulty,few-class;efficiency;neural network;convolutional neural network;transformer;dataset difficulty measurement;scaling law,5.0,3.3333333333333335,Bryan Bo Cao;Lawrence O'Gorman;Michael Coss;Shubham Jain,Nokia networks GmbH;State University of New York at Stony Brook,Intern;Assistant Professor,,,,,
3,3,0.07371062,-0.27021888,0,0.06424707811349922,-0.010531989839880426,"[0.5540547756706123, 0.16512628604105653, 2.869078633820828e-23, 0.28081882302789213, 1.1526043901383049e-07]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,01XV5Za56k,Testing Calibration in Nearly-Linear Time,Calibration;Property testing;Linear programming,6.25,3.25,Lunjia Hu;Arun Jambulapati;Kevin Tian;Chutong Yang,Stanford University;Stanford University;Stanford University;University of Texas at Austin,PhD student;PhD student;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96961,,,https://openreview.net/forum?id=01XV5Za56k,
3,4,-0.1284643,0.3103237,2,-0.09756174176246091,0.3315038065244718,"[0.0005095010573924571, 6.115314244364621e-20, 0.9991714411878863, 5.595376155859921e-10, 0.00031905719518354227]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,01lhHg8H9p,GLBench: A Comprehensive Benchmark for Graph with Large Language Models,Graph learning;Large Language Model;Zero-Shot,6.75,4.0,Yuhan Li;Peisong Wang;Xiao Zhu;Aochuan Chen;Haiyun Jiang;Deng Cai;Victor Wai Kin Chan;Jia Li,"Hong Kong University of Science and Technology;Tsinghua University;Beijing University of Posts and Telecommunications;Hong Kong University of Science and Technology;Tencent AI Lab;Tencent AI Lab;Shenzhen International Graduate School, Tsinghua University;Hong Kong University of Science and Technology",PhD student;MS student;Undergrad student;PhD student;Researcher;Research Scientist;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97881,,,,/media/PosterPDFs/NeurIPS%202024/97881.png?t=1731478194.2539835
3,5,-0.23808402,0.26056772,2,-0.09756174176246091,0.3315038065244718,"[6.893350102058811e-05, 5.46039197744135e-22, 0.9969869948273695, 1.7578394458840217e-09, 0.0029440699137705255]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,01qa1ZJs65,Bridge the Modality and Capability Gaps in Vision-Language Model Selection,Vision-Language Model;Model Selection;Zero-Shot Image Classification,5.25,4.0,Chao Yi;Yuhang He;De-Chuan Zhan;Han-Jia Ye,Nanjing University;Nanjing University;Nanjing University;Nanjing University,MS student;Undergrad student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96960,,,https://openreview.net/forum?id=01qa1ZJs65,/media/PosterPDFs/NeurIPS%202024/96960.png?t=1731123927.9174762
3,6,-0.10493148,-0.30384988,3,-0.15754262445286776,-0.27458739670972204,"[0.11652074101150575, 0.0002481888063976525, 2.0298914094436368e-22, 0.8832106371523653, 2.0433029731106532e-05]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,01s5ODIHKd,FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space,deep watermarking;latent frequency optimization,5.5,3.75,YiYang Guo;Ruizhe Li;Mude Hui;Hanzhong Allan Guo;Chen Zhang;Chuangjian Cai;Le Wan;Shangfei Wang,"University of Science and Technology of China;University of California, Santa Cruz;Renmin University of China;Tsinghua University;University of Science and Technology of China;University of Science and Technology of China",MS student;PhD student;MS student;PhD student;Full Professor;PhD student,https://neurips.cc/virtual/2024/poster/96959,,,https://openreview.net/forum?id=01s5ODIHKd,/media/PosterPDFs/NeurIPS%202024/96959.png?t=1730176108.8718698
3,7,-0.295713,-0.42771262,3,-0.15754262445286776,-0.27458739670972204,"[0.007777066976696999, 8.95939520638976e-07, 1.969778331139795e-27, 0.9922215288158774, 5.082679049591896e-07]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,02CIZ8qeDc,PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection,3D anomaly detection;Zero-shot 3D anomaly detection,6.0,3.6666666666666665,Qihang Zhou;Jiangtao Yan;Shibo He;Wenchao Meng;Jiming Chen,Zhejiang University;Zhejiang University;Zhejiang University;Zhejiang University,PhD student;MS student;Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96958,,,https://openreview.net/forum?id=02CIZ8qeDc,/media/PosterPDFs/NeurIPS%202024/96958.png?t=1731476864.9817398
3,8,-0.3188932,-0.023905918,4,-0.20782917179182095,0.0014387222347446277,"[0.00074871826664632, 9.43241446136876e-15, 7.681109631317387e-06, 0.0008375510832832327, 0.9984060495404298]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,02HWT9c4Lp,Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion,Semantic Scene completion，Voxel Proposal，Knowledge Distillation,5.5,4.0,Lubo Wang;Di Lin;Kairui Yang;Ruonan Liu;Qing Guo;Wuyuan Xie;Miaohui Wang;Lingyu Liang;Yi Wang;Ping Li,"Tianjin University;Tianjin University;Tianjin University;Tianjin University; Agency for Science, Technology and Research (A*STAR));Department of Software Engineering, Shenzhen University;Shenzhen University;South China University of Technology;Shenzhen University;The Hong Kong Polytechnic University",MS student;Associate Professor;PhD student;Associate Professor;Researcher;Associate Professor;Associate Professor;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96957,,,https://openreview.net/forum?id=02HWT9c4Lp,/media/PosterPDFs/NeurIPS%202024/96957.png?t=1731159292.6143699
3,9,0.52375084,0.03593809,1,0.4047695836386393,-0.0824818227172337,"[7.326732677587693e-05, 0.9999267321334593, 4.965791296598374e-17, 5.397649437089583e-10, 1.3666573281987454e-20]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,02r24A8doi,Achieving Constant Regret in Linear Markov Decision Processes,Reinforcement learning;Constant regret;Misspecified linear MDP,5.25,2.75,Weitong Zhang;Zhiyuan Fan;Jiafan He;Quanquan Gu,"Massachusetts Institute of Technology;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles",PhD student;PhD student;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96956,,,https://openreview.net/forum?id=02r24A8doi,
3,10,-0.24769914,0.06194072,4,-0.20782917179182095,0.0014387222347446277,"[0.0019328178822457134, 5.304976464064945e-15, 0.0008095793065375161, 9.456990603564325e-05, 0.9971630329051757]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,04EC4ZnZJj,MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers,transformer architecture;large language model;computational complexity reduction,6.0,3.5,Ning Ding;Yehui Tang;Haochen Qin;Zhenli Zhou;Chao Xu;Lin Li;Kai Han;Liao Heng;Yunhe Wang,"Peking University;Huawei Technologies Ltd.;Huawei Technologies Ltd.;Peking University;Peking University;Huawei Noah's Ark Lab;, Tsinghua University;Huawei Noah's Ark Lab",PhD student;Researcher;Researcher;MS student;Full Professor;Principal Researcher;Principal Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96955,,,https://openreview.net/forum?id=04EC4ZnZJj,
3,11,0.45866024,0.07679337,1,0.4047695836386393,-0.0824818227172337,"[0.003353419288490825, 0.9966465570224328, 5.46416930865532e-13, 2.3688529698442742e-08, 2.319963788366804e-16]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,06JRFVK88O,Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games,Multi-agent Reinforcement Learning;Imitation Learning,6.666666666666667,3.0,The Viet Bui;Tien Anh Mai;Thanh Hong Nguyen,Singapore Management University;University of Oregon;Singapore Management University,Assistant Professor;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96954,,,https://openreview.net/forum?id=06JRFVK88O,/media/PosterPDFs/NeurIPS%202024/96954.png?t=1731744891.8886228
3,12,-0.21952832,-0.2596673,3,-0.15754262445286776,-0.27458739670972204,"[0.039721553495539574, 6.319559226411514e-07, 1.2453609555178713e-17, 0.956279214254968, 0.003998600293569959]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,06Vt6f2js7,SyncTweedies: A General Generative Framework Based on Synchronized Diffusions,Diffusion Models;Synchronization;Texturing;3D Gaussian Splatting;Mesh;Panorama,6.666666666666667,3.6666666666666665,Jaihoon Kim;Juil Koo;Kyeongmin Yeo;Minhyuk Sung,KAIST;Adobe Systems;Korea Advanced Institute of Science & Technology;Korea Advanced Institute of Science & Technology,MS student;Intern;Undergrad student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96953,,,https://openreview.net/forum?id=06Vt6f2js7,
3,13,0.5387558,-0.021885695,1,0.4047695836386393,-0.0824818227172337,"[1.345190856093186e-05, 0.9999865478281601, 1.175417545984968e-20, 2.6327887279727185e-10, 2.0391109203096774e-22]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,07N0qoaZ2L,Improved Analysis for Bandit Learning in Matching Markets,Bandits;Matching markets;Stable matching;Stable regret;Exploration and exploitation;$\alpha$-condition,5.5,3.0,Fang Kong;Zilong Wang;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;John Hopcroft Center, Shanghai Jiao Tong University",PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96952,,,https://openreview.net/forum?id=07N0qoaZ2L,/media/PosterPDFs/NeurIPS%202024/96952.png?t=1731746661.9360106
3,14,-0.31746334,-0.03755091,4,-0.20782917179182095,0.0014387222347446277,"[0.0009269955893381912, 2.6132619774193665e-14, 2.6586174599417543e-06, 0.0014476869445920679, 0.9976226588485837]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,08A6X7FSTs,Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text,Text-to-3D Scene Generation;Latent Diffusion Models,5.5,4.5,Xinyang Li;Zhangyu Lai;Linning Xu;Yansong Qu;Liujuan Cao;Shengchuan Zhang;Bo Dai;Rongrong Ji,Xiamen University;Xiamen University;Xiamen University;Xiamen University;Xiamen University;Shanghai AI Laboratory;Xiamen University;The Chinese University of Hong Kong,PhD student;MS student;PhD student;Full Professor;Assistant Professor;Scientist;Full Professor;Ph.D. student,https://neurips.cc/virtual/2024/poster/96951,,,https://openreview.net/forum?id=08A6X7FSTs,/media/PosterPDFs/NeurIPS%202024/96951.png?t=1732593534.8700738
3,15,0.21572201,0.15297481,0,0.06424707811349922,-0.010531989839880426,"[0.9997474700562877, 0.00019807209939348827, 3.45662407615691e-05, 1.802588378655297e-05, 1.8657197706548311e-06]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,08GbdALmEs,Learning Versatile Skills with Curriculum Masking,reinforcement learning;unsupervised pretraining;masked prediction;curriculum learning,5.25,3.25,Yao Tang;Zhihui Xie;Zichuan Lin;Deheng Ye;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;Tencent AI Lab;Tencent;John Hopcroft Center, Shanghai Jiao Tong University",Undergrad student;MS student;Researcher;Principal Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96950,,,https://openreview.net/forum?id=08GbdALmEs,/media/PosterPDFs/NeurIPS%202024/96950.png?t=1733319308.3295946
3,16,-0.17784788,-0.16018736,3,-0.15754262445286776,-0.27458739670972204,"[0.15271465716610208, 3.720532748703037e-07, 1.7376613896122336e-12, 0.6377003995713947, 0.2095845712074907]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,08nbMTxazb,Chicks4FreeID: A Benchmark Dataset for Chicken Re-Identification,animal re-identification;chicken re-identification;chicken dataset;re-identification dataset;benchmark dataset;closed-set re-identification;computer vision;chicken instance segmentation;poultry;livestock,4.75,4.0,Daria Kern;Tobias Schiele;Ulrich Klauck;Winfred Ingabire,Glasgow Caledonian University;Hochschule Aalen;Glasgow Caledonian University,PhD student;Full Professor;Lecturer,,,,,
3,17,0.12485067,-0.17534988,0,0.06424707811349922,-0.010531989839880426,"[0.7330050578488061, 0.1923208616582887, 2.2547985426972052e-18, 0.07467339193791842, 6.885549866721186e-07]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,08oUnmtj8Q,FSEO: A Few-Shot Evolutionary Optimization Framework for Expensive Multi-Objective Optimization and Constrained Optimization,Expensive optimization;few-shot optimization;multi-objective optimization;constrained optimization;surrogate-assisted evolutionary optimization,4.5,3.5,Xunzhao Yu,,,,,,,
3,18,-0.045080878,-0.32160506,3,-0.15754262445286776,-0.27458739670972204,"[0.2165902382410717, 0.004078945648268737, 1.3361088548260414e-24, 0.7793297630244664, 1.0530861932048667e-06]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,09RKw0vXjR,Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations,feature selection;sparse coding;dictionary learning;compressed sensing;iterative hard thresholding;pruning method,5.75,3.0,Yasutoshi Ida;Sekitoshi Kanai;Atsutoshi Kumagai;Tomoharu Iwata;Yasuhiro Fujiwara,NTT;NTT;NTT;NTT;NTT,Researcher;Researcher;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96949,,,https://openreview.net/forum?id=09RKw0vXjR,/media/PosterPDFs/NeurIPS%202024/96949.png?t=1733375377.8112724
3,19,-0.29219365,-0.1354431,4,-0.20782917179182095,0.0014387222347446277,"[0.011496657772004948, 1.1556557393114665e-10, 5.688517075044706e-10, 0.11515105114935575, 0.873352290394222]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,09nyBqSdUz,RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance,Consistent image generation;Diverse image generation;Improve temporal-consistency;Feature injection from multiple images,5.5,4.0,Jiaojiao Fan;Haotian Xue;Qinsheng Zhang;Yongxin Chen,Georgia Institute of Technology;Georgia Institute of Technology;Georgia Institute of Technology;NVIDIA,PhD student;PhD student;Associate Professor;Research Intern,https://neurips.cc/virtual/2024/poster/96948,,,https://openreview.net/forum?id=09nyBqSdUz,/media/PosterPDFs/NeurIPS%202024/96948.png?t=1731392354.7708242
3,20,0.22983314,0.005944166,0,0.06424707811349922,-0.010531989839880426,"[0.8966876010307098, 0.10244441965604908, 7.412828584361577e-11, 0.0008677116992384849, 2.675398743520763e-07]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0AumdfLzpK,A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations,Visual Reinforcement Learning;Generalization,6.0,4.0,Wonil Song;Hyesong Choi;Kwanghoon Sohn;Dongbo Min,Yonsei Univ.;Ewha Womans University;Yonsei University;Ewha Womans University,PhD student;PhD student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96947,,,https://openreview.net/forum?id=0AumdfLzpK,/media/PosterPDFs/NeurIPS%202024/96947.png?t=1732451612.1247888
3,21,-0.2313607,0.15489271,4,-0.20782917179182095,0.0014387222347446277,"[0.003084708744160771, 5.961739056191591e-17, 0.2711250843840596, 5.4659092939467975e-06, 0.7257847409624856]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0AwMciNShl,"Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality",Human evaluation;text-to-video models,5.25,4.0,Tianle Zhang;Langtian Ma;Yuchen Yan;Yuchen Zhang;Yue Yang;Ziyao Guo;Wenqi Shao;Kai Wang;Yang You;Yu Qiao;Ping Luo;Kaipeng Zhang,University of Electronic Science and Technology of China;Southern University of Science and Technology;The University of Nottingham Ningbo China;University of Electronic Science and Technology of China;Xidian University;Shanghai AI Laboratory;National University of Singapore;National University of Singapore;Shanghai AI Laboratory;The University of Hong Kong;Shanghai Jiaotong University,Undergrad student;Undergrad student;Undergrad student;Undergrad student;MS student;Researcher;PhD student;Professor;Researcher;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96946,,,https://openreview.net/forum?id=0AwMciNShl,/media/PosterPDFs/NeurIPS%202024/96946.png?t=1729079669.652648
3,22,0.44196302,-0.22339565,1,0.4047695836386393,-0.0824818227172337,"[5.580710659305055e-05, 0.9999441261882436, 1.966001002206042e-30, 6.670516338440323e-08, 1.444066451765362e-21]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0C3bLHwjsY,Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions,Online Matching;Competitive Analysis;Fairness Maximization,6.25,3.0,Will Ma;Pan Xu,Columbia University;New Jersey Institute of Technology,Assistant Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96945,,,https://openreview.net/forum?id=0C3bLHwjsY,/media/PosterPDFs/NeurIPS%202024/96945.png?t=1731641014.5806563
3,23,0.31953293,-0.23248373,1,0.4047695836386393,-0.0824818227172337,"[0.0023885106674247873, 0.9975890954840138, 1.5294395139565538e-27, 2.239384856105481e-05, 5.3550326864206295e-16]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0DE1dLMW2b,Quantum algorithm for large-scale market equilibrium computation,market equilibrium computation;quantum algorithm,6.0,2.75,Po-Wei Huang;Patrick Rebentrost,Centre for Quantum Technologies;National University of Singapore,Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96944,,,https://openreview.net/forum?id=0DE1dLMW2b,/media/PosterPDFs/NeurIPS%202024/96944.png?t=1731426989.5298698
3,24,0.0025802255,-0.08199731,0,0.06424707811349922,-0.010531989839880426,"[0.8853857184222425, 0.0001531713440767954, 2.5612223691279332e-11, 0.10494869835719906, 0.009512411850869403]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0EfUYVMrLv,Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment,non-stationary environments;continuous distribution shift;test-time adaptation;unlabeled data,6.666666666666667,4.0,Zhen-Yu Zhang;Zhiyu Xie;Huaxiu Yao;Masashi Sugiyama,"RIKEN;Stanford University;Department of Computer Science, University of North Carolina at Chapel Hill;The University of Tokyo",Postdoc;MS student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96943,,,https://openreview.net/forum?id=0EfUYVMrLv,/media/PosterPDFs/NeurIPS%202024/96943.png?t=1731687693.6296034
3,25,0.023439856,-0.079839304,0,0.06424707811349922,-0.010531989839880426,"[0.9155852733944438, 0.00034161023218550244, 1.4591115588054193e-11, 0.0801643189614268, 0.0039087973973526485]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0G0VpMjKyV,Sketching for Distributed Deep Learning: A Sharper Analysis,sketching;distributed learning;federated learning;optimization,5.666666666666667,4.0,Mayank Shrivastava;Berivan Isik;Qiaobo Li;Sanmi Koyejo;Arindam Banerjee,"University of Illinois, Urbana Champaign;Stanford University;Department of Computer Science, University of Illinois at Urbana-Champaign;University of Illinois, Urbana Champaign;Google",MS student;PhD student;PhD student;Professor;Research Scientist,https://neurips.cc/virtual/2024/poster/96942,,,https://openreview.net/forum?id=0G0VpMjKyV,/media/PosterPDFs/NeurIPS%202024/96942.png?t=1733481266.9121125
3,26,-0.06371302,0.3954228,2,-0.09756174176246091,0.3315038065244718,"[0.0004614819850606218, 4.4664327243240315e-21, 0.9995367035972839, 4.556799878353306e-12, 1.8144130984625217e-06]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,0G5OK5vmmg,WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts,Benchmark;Large Language Models;Classical Chinese Literature and Language Arts,6.25,2.75,Jiahuan Cao;Yang Liu;Yongxin Shi;Kai Ding;Lianwen Jin,South China University of Technology;South China University of Technology;South China University of Technology;INTSIG Information;South China University of Technology,MS student;MS student;PhD student;Researcher;Professor,https://neurips.cc/virtual/2024/poster/97880,,,,/media/PosterPDFs/NeurIPS%202024/97880.png?t=1730896668.2191207
3,27,-0.2963673,0.015343715,4,-0.20782917179182095,0.0014387222347446277,"[0.000800430371701634, 3.171084223686763e-15, 7.814720788241362e-05, 0.00024840267992218507, 0.9988730197404907]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0G8AXwtmy2,T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition,harmful dataset;harmful content detection;Vision Language Model,6.5,3.75,Chen Yeh;You-Ming Chang;Wei-Chen Chiu;Ning Yu,National Yang Ming Chiao Tung University;National Yang Ming Chiao Tung University;National Chiao Tung University,MS student;MS student;Associate Professor,https://neurips.cc/virtual/2024/poster/97879,,,,/media/PosterPDFs/NeurIPS%202024/97879.png?t=1730218737.4487233
3,28,0.08612508,0.3898904,2,-0.09756174176246091,0.3315038065244718,"[0.019419535232385945, 3.100764338372388e-15, 0.9805802171585448, 7.05327371662652e-11, 2.4753853340751785e-07]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,0Gl5WxY6es,Grounding Multimodal Large Language Models in Actions,Embodied AI;Multimodal Large Language Models;Reinforcement Learning;Imitation Learning,6.0,3.6666666666666665,Andrew Szot;Bogdan Mazoure;Harsh Agrawal;R Devon Hjelm;Zsolt Kira;Alexander T Toshev,Georgia Institute of Technology;Apple;Apple;Apple;Georgia Institute of Technology;Apple,PhD student;Research Scientist;Researcher;Researcher;Assistant Professor;research scientist,https://neurips.cc/virtual/2024/poster/96941,,,https://openreview.net/forum?id=0Gl5WxY6es,
3,29,-0.20296153,0.2345368,2,-0.09756174176246091,0.3315038065244718,"[0.0006439113339536239, 2.530459390173495e-19, 0.977690600472945, 3.799652935840037e-08, 0.02166545019657215]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,0Gmi8TkUC7,GenAI Arena: An Open Evaluation Platform for Generative Models,Evaluation;Benchmark;Platform;Generative Model,6.0,3.5,Dongfu Jiang;Max Ku;Tianle Li;Yuansheng Ni;Shizhuo Sun;Rongqi Fan;Wenhu Chen,Allen Institute for Artificial Intelligence;University of Waterloo;University of Waterloo;University of Toronto;NVIDIA;University of Waterloo,Intern;MS student;MS student;Undergrad student;Intern;Assistant Professor,https://neurips.cc/virtual/2024/poster/97878,,,,/media/PosterPDFs/NeurIPS%202024/97878.png?t=1730329031.3167162
3,30,-0.3021013,-0.23802479,3,-0.15754262445286776,-0.27458739670972204,"[0.018092396920364157, 7.881977595617187e-09, 7.636636366671074e-15, 0.9344189435611695, 0.047488651636481166]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,0HRRNEAQFp,A General Protocol to Probe Large Vision Models for 3D Physical Understanding,3D physical scene understanding; Representation probing protocol; Benchmark and evaluation,6.333333333333333,4.0,Guanqi Zhan;Chuanxia Zheng;Weidi Xie;Andrew Zisserman,University of Oxford;University of Oxford;Shanghai Jiaotong University,PhD student;Postdoc;Associate Professor,https://neurips.cc/virtual/2024/poster/96940,,,https://openreview.net/forum?id=0HRRNEAQFp,/media/PosterPDFs/NeurIPS%202024/96940.png?t=1731705235.0575316
3,31,0.40233114,0.06031101,1,0.4047695836386393,-0.0824818227172337,"[0.02491644955344819, 0.9750829501404171, 3.267095711390189e-12, 6.003027558020909e-07, 1.1168265022099398e-13]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0JSKjdePGq,When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL,reinforcement learning;continuous-time,6.75,3.25,Lenart Treven;Bhavya Sukhija;Yarden As;Florian Dorfler;Andreas Krause,"Swiss Federal Institute of Technology;ETHZ - ETH Zurich;Department of Computer Science, ETHZ - ETH Zurich;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96939,,,https://openreview.net/forum?id=0JSKjdePGq,/media/PosterPDFs/NeurIPS%202024/96939.png?t=1730197260.75527
3,32,-0.31179968,-0.050893012,4,-0.20782917179182095,0.0014387222347446277,"[0.001279341308512437, 9.412485133941198e-14, 8.310825655940648e-07, 0.002621002410347843, 0.9960988251984801]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0KseSacluJ,CoFie: Learning Compact Neural Surface Representations with Coordinate Fields,Neural Surface Representation;Shape Auto-Decoding;Coordinate Field.,5.0,4.0,Hanwen Jiang;Haitao Yang;Georgios Pavlakos;Qixing Huang,University of Texas at Austin;The University of Texas at Austin;University of Texas at Austin;University of Texas at Austin,PhD student;PhD student;Assistant Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96938,,,https://openreview.net/forum?id=0KseSacluJ,
3,33,0.11298243,0.035079706,0,0.06424707811349922,-0.010531989839880426,"[0.9972984317835001, 0.00023277329829547787, 5.6464573544933746e-08, 0.002088250031294428, 0.0003804884223366036]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0KvYLaTBTE,Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference,Generative models;Reinforcement learning;Decision transformer,6.333333333333333,3.0,Deqian Kong;Dehong Xu;Minglu Zhao;Bo Pang;Jianwen Xie;Andrew Lizarraga;Yuhao Huang;Sirui Xie;Ying Nian Wu,"University of California, Los Angeles;Amazon;University of California, Los Angeles;University of California, Los Angeles;Xi'an Jiaotong University;University of California, Los Angeles;University of California, Los Angeles;UCLA",PhD student;Intern;PhD student;PhD student;PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96937,,,https://openreview.net/forum?id=0KvYLaTBTE,
3,34,-0.23456638,0.06657637,4,-0.20782917179182095,0.0014387222347446277,"[0.0026530766595769923, 1.0543624880700657e-14, 0.0008983937919402569, 9.915529533079944e-05, 0.9963493742531412]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0LXotew9Du,KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization,Quantization;KV Cache;LLM Inference;Compression;Long Context Length,6.25,3.25,Coleman Richard Charles Hooper;Sehoon Kim;Hiva Mohammadzadeh;Michael W. Mahoney;Sophia Shao;Kurt Keutzer;Amir Gholami,"University of California, Berkeley;University of California, Berkeley;University of California, Berkeley;University of California, Berkeley",PhD student;PhD student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96936,,,https://openreview.net/forum?id=0LXotew9Du,
3,35,0.11017645,-0.16371755,0,0.06424707811349922,-0.010531989839880426,"[0.8149446854054475, 0.09699659848438598, 2.021347393167096e-17, 0.0880559624413695, 2.7536687969786346e-06]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0Lb8vZT1DB,Reliable Learning of Halfspaces under Gaussian Marginals,reliable learning;agnostic learning;halfspace;proper leaning;statistical query,7.25,2.25,Ilias Diakonikolas;Lisheng Ren;Nikos Zarifis,"University of Wisconsin - Madison;University of Wisconsin - Madison;University of Wisconsin, Madison",Full Professor;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96935,,,https://openreview.net/forum?id=0Lb8vZT1DB,
3,36,0.1429859,0.059452157,0,0.06424707811349922,-0.010531989839880426,"[0.9988131752587486, 0.00034064126632603813, 1.8309205731800002e-07, 0.0007506201583555041, 9.53802245125168e-05]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0LfgE6kvKZ,Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning,Federated Learning; Model Merging,5.0,3.6666666666666665,Minghui Chen;Meirui Jiang;Xin Zhang;Qi Dou;Zehua Wang;Xiaoxiao Li,"University of British Columbia;Meta Facebook;The Chinese University of Hong Kong;University of British Columbia;University of British Columbia;Department of Computer Science and Engineering, The Chinese University of Hong Kong",PhD student;Research Scientist;Assistant Professor;Researcher;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96934,,,https://openreview.net/forum?id=0LfgE6kvKZ,/media/PosterPDFs/NeurIPS%202024/96934.png?t=1731518093.5294044
3,37,-0.040502112,0.02318828,0,0.06424707811349922,-0.010531989839880426,"[0.6769641957154445, 2.514490190897798e-07, 3.1565363189535605e-06, 0.011819882823631424, 0.31121251347558593]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0Lr9HQijA1,Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations,Imprecise Label Learning,5.75,3.0,Hao Chen;Ankit Shah;Jindong Wang;Ran Tao;Yidong Wang;Xiang Li;Xing Xie;Masashi Sugiyama;Rita Singh;Bhiksha Raj,"Carnegie Mellon University;Accenture;Microsoft Research;Peking University;Microsoft Research Asia;The University of Tokyo;School of Computer Science, Carnegie Mellon University;Mohamed bin Zayed University of Artificial Intelligence",PhD student;Principal Researcher;Researcher;PhD student;Senior Principal Researcher;Full Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96933,,,https://openreview.net/forum?id=0Lr9HQijA1,/media/PosterPDFs/NeurIPS%202024/96933.png?t=1731704880.9846606
3,38,-0.06471333,0.08954511,4,-0.20782917179182095,0.0014387222347446277,"[0.3626088339198052, 1.6169119486316666e-09, 0.0008748371714432614, 0.0011985897425328214, 0.6353177375493068]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0MXzbAv8xy,GFT: Graph Foundation Model with Transferable Tree Vocabulary,Graph Foundation Model;Transferability;Computation Tree;Graph Neural Network,6.0,3.75,Zehong Wang;Zheyuan Zhang;Nitesh V Chawla;Chuxu Zhang;Yanfang Ye,University of Notre Dame;University of Notre Dame;University of Notre Dame;University of Notre Dame,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96932,,,https://openreview.net/forum?id=0MXzbAv8xy,
3,39,0.06407858,0.09707585,0,0.06424707811349922,-0.010531989839880426,"[0.9926084975435718, 1.5673122963466187e-06, 4.9665204711064994e-05, 0.0006319438014886191, 0.0067083261379320145]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0NMzBwqaAJ,Not All Tokens Are What You Need for Pretraining,pre-training;next token prediction;data optimization;data selection,7.666666666666667,4.0,Zhenghao Lin;Zhibin Gou;Yeyun Gong;Xiao Liu;yelong shen;Ruochen Xu;Chen Lin;Yujiu Yang;Jian Jiao;Nan Duan;Weizhu Chen,Xiamen University;Microsoft;Microsoft Research Asia;Microsoft Research;Xiamen University;Tsinghua University;Microsoft;Microsoft Research Asia;Microsoft GenAI,MS student;Intern;Researcher;Researcher;Full Professor;Full Professor;Principal Researcher;Principal Researcher;Vice President,https://neurips.cc/virtual/2024/poster/96931,,,https://openreview.net/forum?id=0NMzBwqaAJ,/media/PosterPDFs/NeurIPS%202024/96931.png?t=1733724962.7310221
3,40,-0.021407472,0.09407413,0,0.06424707811349922,-0.010531989839880426,"[0.7604444375793826, 2.2123062220687637e-08, 0.0005471440920292662, 0.0013732393991213476, 0.23763515680640454]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0NQzQVu9tY,DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors,representation learning;offline reinforcement learning;behavioral cloning;visual distractor,7.0,3.0,Joseph Ortiz;Antoine Dedieu;Wolfgang Lehrach;J Swaroop Guntupalli;Carter Wendelken;Ahmad Humayun;Sivaramakrishnan Swaminathan;Guangyao Zhou;Miguel Lazaro-Gredilla;Kevin Patrick Murphy,Google DeepMind;Google DeepMind;Google Deepmind;Google DeepMind;Google;Google DeepMind;Google DeepMind;Google DeepMind;Google Deepmind;Google,Researcher;Researcher;Researcher;Researcher;Researcher;Researcher;Research Engineer;Research Scientist;Research Scientist;Principal Researcher,https://neurips.cc/virtual/2024/poster/97877,,,,/media/PosterPDFs/NeurIPS%202024/97877.png?t=1733266397.4133346
3,41,-0.056248758,0.025906589,0,0.06424707811349922,-0.010531989839880426,"[0.5226471972857129, 8.326628985455477e-08, 5.6170673702892075e-06, 0.010118640680309411, 0.4672284617003176]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0SMhqvgHST,EEVEE and GATE: Finding the right benchmarks and how to run them seamlessly,multi-modal;benchmarks;machine learning;model evaluation;benchmark frameworks,6.0,4.0,Antreas Antoniou;Eleni Triantafillou;Hugo Larochelle;Sebastien Montella;Fady Rezk;Kiyoon Kim;Linus Ericsson;Pavlos Vougiouklis;Justin Engelmann;Elliot J. Crowley;Srihari Humbarwadi;Yi Liu;Guang Yang;Jeff Z. Pan;Amos Storkey,"Google;Google;Huawei Technologies Ltd.;Samsung;Deargen;University of Edinburgh, University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh, University of Edinburgh;University of Edinburgh",Researcher;Research Scientist;Researcher;Intern;Researcher;Postdoc;Researcher;Assistant Professor;Researcher;Full Professor;Full Professor,,,,,
3,42,-0.15132618,0.02146309,4,-0.20782917179182095,0.0014387222347446277,"[0.03599746564236687, 8.93215266446921e-11, 1.1404244707644532e-05, 0.0022015864552579097, 0.9617895435683461]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0SRJBtTNhX,IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors,Graph Machine Learning;Graph Data Augmentation;Graph Neural Networks,5.5,4.0,Shenghe Zheng;Hongzhi Wang;Xianglong Liu,Harbin Institute of Technology;Harbin Institute of Technology;Harbin Institute of Technology,MS student;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96930,,,https://openreview.net/forum?id=0SRJBtTNhX,/media/PosterPDFs/NeurIPS%202024/96930.png?t=1732617637.3891017
3,43,-0.18518934,0.0027779788,4,-0.20782917179182095,0.0014387222347446277,"[0.015355424694381243, 2.082118752646836e-11, 4.058745057497177e-06, 0.0022199719960291895, 0.9824205445437109]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0T8xRFrScB,Benchmarking Counterfactual Image Generation,benchmark;causal inference;counterfactual image generation,7.25,3.75,Thomas Melistas;Nikos Spyrou;Nefeli Gkouti;Pedro Sanchez;Athanasios Vlontzos;Yannis Panagakis;Giorgos Papanastasiou;Sotirios A. Tsaftaris,"University of Athens;University of Athens;University of Athens;University of Edinburgh, University of Edinburgh;Spotify;Pfizer;University of Edinburgh",PhD student;PhD student;PhD student;PhD student;Researcher;Principal Researcher;Professor in machine learning and computer vision,https://neurips.cc/virtual/2024/poster/97876,,,,/media/PosterPDFs/NeurIPS%202024/97876.png?t=1731712408.6398222
3,44,0.5118622,-0.024860546,1,0.4047695836386393,-0.0824818227172337,"[3.700075619512428e-05, 0.9999629980766174, 4.399067716879092e-20, 1.1671875302464286e-09, 5.2742310937400324e-21]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0TUMAAb3of,Queueing Matching Bandits with Preference Feedback,Bandits;Queue;Preference Feedback,6.0,2.5,Jung-hun Kim;Min-hwan Oh,Seoul National University;Seoul National University,Assistant Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96929,,,https://openreview.net/forum?id=0TUMAAb3of,/media/PosterPDFs/NeurIPS%202024/96929.png?t=1733803835.532587
3,45,-0.0018669573,0.3644946,2,-0.09756174176246091,0.3315038065244718,"[0.004238440405478118, 1.9286311841487488e-17, 0.995755879956361, 1.1888511994619812e-10, 5.679519275715504e-06]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,0VeSCjRDBy,Adversarial Moment-Matching Distillation of Large Language Models,Knowledge distillation;Large language models;Imitation learning;Moment-matching;Adversarial training,6.25,3.0,Chen Jia,,,https://neurips.cc/virtual/2024/poster/96928,,,https://openreview.net/forum?id=0VeSCjRDBy,/media/PosterPDFs/NeurIPS%202024/96928.png?t=1731660620.7591212
3,46,-0.24925767,0.015651966,4,-0.20782917179182095,0.0014387222347446277,"[0.002362449553954891, 8.380097577633626e-14, 2.9207974165244294e-05, 0.00046028834931201307, 0.997148054122484]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0WCFI2Qx85,ScaleKD: Strong Vision Transformers Could Be Excellent Teachers,knowledge distillation;model compression;training acceleration;vision transformer;convolutional neural network;multi-layer perception,6.25,4.5,Jiawei Fan;Chao Li;Xiaolong Liu;Anbang Yao,Intel Labs China;Intel;Intel,Research Intern;Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96927,,,https://openreview.net/forum?id=0WCFI2Qx85,/media/PosterPDFs/NeurIPS%202024/96927.png?t=1731695837.2500114
3,47,0.2804453,-0.1894261,1,0.4047695836386393,-0.0824818227172337,"[0.013613574812307032, 0.9862220421448421, 1.698244233117417e-23, 0.00016438304247181997, 3.790169368374354e-13]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0XKvW4ijxp,Learning-Augmented Algorithms with Explicit Predictors,online algorithms;learning-augmented algorithms;scheduling;caching,6.0,4.0,Marek Elias;Haim Kaplan;Yishay Mansour;Shay Moran,"Bocconi University;Technion, Technion;School of Computer Science, Tel Aviv University",Assistant Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96926,,,https://openreview.net/forum?id=0XKvW4ijxp,/media/PosterPDFs/NeurIPS%202024/96926.png?t=1733319671.0065775
3,48,0.37225774,-0.11562894,1,0.4047695836386393,-0.0824818227172337,"[0.001658765112262976, 0.9983392100026898, 1.6726008548059357e-21, 2.0248850461398172e-06, 1.1194591157943853e-15]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0XeNkkENuI,The Road Less Scheduled,Stochastic Optimization;Optimization;Convex Optimization;Learning Rates;Learning Rate Schedules,7.5,3.5,Aaron Defazio;Xingyu Alice Yang;Ahmed Khaled;Konstantin Mishchenko;Harsh Mehta;Ashok Cutkosky,Meta;Meta;Princeton University;Samsung;Google Research;Boston University,Research Scientist;Research Engineer;PhD student;Researcher;Software Engineer;Assistant Professor,https://neurips.cc/virtual/2024/poster/96925,,,https://openreview.net/forum?id=0XeNkkENuI,/media/PosterPDFs/NeurIPS%202024/96925.png?t=1730837481.9895687
3,49,0.1460578,0.21914145,0,0.06424707811349922,-0.010531989839880426,"[0.9853103416650588, 2.0433972707516838e-07, 0.014633782447896669, 3.709828758916542e-06, 5.196171855836851e-05]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0ZZMUjZJYF,Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study,LLMs;Learning by Teaching;Reasoning;Mathematical Reasoning;Code Synthesis;Weak-to-Strong Generalization;In-Context Learning;Prompting;Knowledge Distillation;Education-Inspired,6.5,4.0,Xuefei Ning;Zifu Wang;Shiyao Li;Zinan Lin;Peiran Yao;Tianyu Fu;Matthew B. Blaschko;Guohao Dai;Huazhong Yang;Yu Wang,Tsinghua University;KU Leuven;Tsinghua University;Microsoft;Infinigence;Shanghai Jiaotong University;Tsinghua University;Tsinghua University;KU Leuven,Research Assistant Professor;PhD student;PhD student;Senior Researcher;Researcher;Associate Professor;Full Professor;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96924,,,https://openreview.net/forum?id=0ZZMUjZJYF,/media/PosterPDFs/NeurIPS%202024/96924.png?t=1732367562.4969194
3,50,0.07159563,-0.024327766,0,0.06424707811349922,-0.010531989839880426,"[0.9836127423375638, 0.00037043779110242965, 8.324115459588309e-10, 0.014685983177138396, 0.001330835861783819]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0ZeONp33f0,Graph Neural Networks and Arithmetic Circuits,Machine Learning;Graph Neural Networks;Arithmetic Circuits;Computational Complexity,6.5,3.25,Timon Barlag;Vivian Holzapfel;Laura Strieker;Jonni Virtema;Heribert Vollmer,Universität Hannover;Leibniz Universität Hannover;Leibniz Universität Hannover;University of Sheffield;Leibniz Universität Hannover,PhD student;Undergrad student;PhD student;Lecturer;Full Professor,https://neurips.cc/virtual/2024/poster/96923,,,https://openreview.net/forum?id=0ZeONp33f0,/media/PosterPDFs/NeurIPS%202024/96923.png?t=1732106485.9402945
3,51,-0.078428976,-0.18954016,3,-0.15754262445286776,-0.27458739670972204,"[0.3471354273928223, 9.17385537147547e-05, 1.0551363969810568e-15, 0.6486804651947079, 0.004092368858753935]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,0aN7VWwp4g,Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting,Precipitation Nowcasting;Video Prediction;Fourier Analysis;Loss Function,6.0,4.0,Chiu-Wai Yan;Shi Quan Foo;Van-Hoan Trinh;Dit-Yan Yeung;Ka-Hing Wong;Wai-Kin Wong,Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology,Chair Professor;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96922,,,https://openreview.net/forum?id=0aN7VWwp4g,/media/PosterPDFs/NeurIPS%202024/96922.png?t=1731480203.951872
3,52,-0.23586994,0.37846398,2,-0.09756174176246091,0.3315038065244718,"[4.077535830884939e-06, 3.0796286271579405e-27, 0.9999924764042072, 3.510635088658198e-13, 3.4460596109162116e-06]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,0bFXbEMz8e,FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions,generative models;material generation;chemistry;flow matching;large language models,6.0,4.333333333333333,Anuroop Sriram;Benjamin Kurt Miller;Ricky T. Q. Chen;Brandon M Wood,"Meta Facebook;University of Amsterdam;FAIR at Meta;FAIR Labs, Meta AI",Principal Researcher;PhD student;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96921,,,https://openreview.net/forum?id=0bFXbEMz8e,/media/PosterPDFs/NeurIPS%202024/96921.png?t=1730973273.143089
3,53,-0.15925287,-0.015642455,4,-0.20782917179182095,0.0014387222347446277,"[0.04204192557811869, 4.594061190125601e-10, 7.230281470434985e-07, 0.007438631295007234, 0.950518719639321]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0bINeW40u4,Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning,Medical Multi-modal Alignment;Eye-gaze;Radiology,6.25,3.5,Chong Ma;Hanqi Jiang;Wenting Chen;Yiwei Li;Zihao Wu;Xiaowei Yu;Zhengliang Liu;Lei Guo;Dajiang Zhu;Tuo Zhang;Dinggang Shen;Tianming Liu;Xiang Li,"Northwest Polytechnical University Xi'an;Beijing Jiaotong University;City University of Hong Kong;University of Georgia;University of Georgia;University of Texas at Arlington, University of Texas at Arlington;University of Georgia;University of Texas at Arlington;Northwestern Polytechnical University;ShanghaiTech University;University of Georgia;Massachusetts General Hospital, Harvard University",PhD student;Undergrad student;PhD student;PhD student;PhD student;PhD student;PhD student;Assistant Professor;Associate Professor;Full Professor;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96920,,,https://openreview.net/forum?id=0bINeW40u4,
3,54,0.38273144,-0.19184409,1,0.4047695836386393,-0.0824818227172337,"[0.00044957429662353753, 0.9995493090905069, 1.1327973599649384e-26, 1.1166128695563306e-06, 6.142839774115198e-18]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0cSQ1Sg7db,Generalization of Hamiltonian algorithms,Generalization;stochastic algorithms;concentration inequalities;PAC-Bayes,6.5,3.0,Andreas Maurer,,,https://neurips.cc/virtual/2024/poster/96919,,,https://openreview.net/forum?id=0cSQ1Sg7db,
3,55,-0.029614072,-0.05991212,0,0.06424707811349922,-0.010531989839880426,"[0.8413459461902179, 1.7081000254475644e-05, 9.251644165791043e-10, 0.094581492810956, 0.06405547907340733]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0cgDDa4OFr,Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation,source distribution estimation;maximum entropy;Sliced-Wasserstein distance;empirical Bayes;simulation-based inference,5.8,2.8,Julius Vetter;Guy Moss;Cornelius Schröder;Richard Gao;Jakob H. Macke,Eberhard-Karls-Universität Tübingen;Eberhard-Karls-Universität Tübingen;University Tübingen;Eberhard-Karls-Universität Tübingen,PhD student;PhD student;Postdoc;Postdoc,https://neurips.cc/virtual/2024/poster/96918,,,https://openreview.net/forum?id=0cgDDa4OFr,/media/PosterPDFs/NeurIPS%202024/96918.png?t=1733318904.6928847
3,56,-0.041920777,-0.1336057,0,0.06424707811349922,-0.010531989839880426,"[0.6502330026286735, 0.00011402765477960545, 3.5369483664461623e-13, 0.3379266084612229, 0.011726361254970287]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0d50Il6enG,Non-parametric classification via expand-and-sparsify representation,non-parametric regression;non-parametric classification;expand-and-sparsify representation;universal consistency;minimax-optimal convergence rate,6.0,3.0,Kaushik Sinha,Wichita State University,Associate Professor,https://neurips.cc/virtual/2024/poster/96917,,,https://openreview.net/forum?id=0d50Il6enG,/media/PosterPDFs/NeurIPS%202024/96917.png?t=1731697679.5420048
3,57,-0.05421332,-0.22073112,3,-0.15754262445286776,-0.27458739670972204,"[0.3365824778432611, 0.0005072944430936564, 5.848974004530687e-18, 0.6625164118135926, 0.0003938159000527032]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,0dtA21q83C,DeNetDM: Debiasing by Network Depth Modulation,Trustworthy Machine Learning;Debiasing;Robustness,6.0,3.5,Silpa Vadakkeeveetil Sreelatha;Adarsh Kappiyath;Abhra Chaudhuri;Anjan Dutta,University of Surrey;University of Exeter;University of Surrey,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96916,,,https://openreview.net/forum?id=0dtA21q83C,/media/PosterPDFs/NeurIPS%202024/96916.png?t=1733689557.490417
3,58,-0.19589648,0.09422963,4,-0.20782917179182095,0.0014387222347446277,"[0.007368447256537867, 3.8946333659450733e-14, 0.0036547023749689887, 7.848813392133844e-05, 0.988898362234533]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0e5uOaJxo1,Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure,Graph Neural Network;Protein Sequence;Structure,5.0,3.3333333333333335,Bozhen Hu;Cheng Tan;Jun Xia;Yue Liu;Lirong Wu;Jiangbin Zheng;Yongjie Xu;Yufei Huang;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University, China;National University of Singapore;Westlake University;Westlake University;Westlake University;Zhejiang University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96915,,,https://openreview.net/forum?id=0e5uOaJxo1,/media/PosterPDFs/NeurIPS%202024/96915.png?t=1730385968.8958924
3,59,0.09615892,0.18102637,0,0.06424707811349922,-0.010531989839880426,"[0.9927400134268634, 1.1490319812670384e-07, 0.006198973354499426, 2.662082076742712e-05, 0.0010342774946716046]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0feJEykDRx,Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models,spatial-temporal data mining;location-based service;check-in sequence;large language model,5.75,4.0,Letian Gong;Yan Lin;Xinyue Zhang;Yiwen Lu;Xuedi Han;Yichen Liu;Shengnan Guo;Youfang Lin;Huaiyu Wan,Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University,PhD student;PhD student;Undergrad student;Undergrad student;MS student;Associate Professor;Full Professor;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96914,,,https://openreview.net/forum?id=0feJEykDRx,/media/PosterPDFs/NeurIPS%202024/96914.png?t=1731289337.5941467
3,60,-0.013711061,-0.07216554,0,0.06424707811349922,-0.010531989839880426,"[0.8710504487671247, 5.432021141714783e-05, 1.39608627177932e-10, 0.10395599134687256, 0.024939239534977085]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0jld45XGgJ,Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?,neural collapse;deep neural collapse;unconstrained features model;deep unconstrained features model;low-rank bias,6.5,3.75,Peter Súkeník;Christoph H. Lampert;Marco Mondelli,Institute of Science and Technology;Institute of Science and Technology Austria;Institute of Science and Technology Austria,PhD student;Assistant Professor;Professor,https://neurips.cc/virtual/2024/poster/96913,,,https://openreview.net/forum?id=0jld45XGgJ,
3,61,0.49365819,-0.019841706,1,0.4047695836386393,-0.0824818227172337,"[8.318205328009704e-05, 0.9999168147874918, 2.744599478830273e-19, 3.159227991271975e-09, 6.228354898887533e-20]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0l9yGPTHAU,Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms,Robust Markov decision process;norm;sample complexity;strong duality,6.5,3.0,Pierre Clavier;Laixi Shi;Erwan Le Pennec;Eric Mazumdar;Adam Wierman;Matthieu Geist,"École Polytechnique;California Institute of Technology;Ecole polytechnique;Deparment of Computing + Mathematical Sciences, California Institute of Technology;California Institute of Technology;Google",PhD student;Postdoc;Full Professor;Assistant Professor;Professor;Researcher,https://neurips.cc/virtual/2024/poster/96912,,,https://openreview.net/forum?id=0l9yGPTHAU,
3,62,-0.096782275,0.2680031,2,-0.09756174176246091,0.3315038065244718,"[0.005818890346623792, 9.099601237594967e-17, 0.9899940609848876, 3.283728311864456e-08, 0.004187015831205356]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,0lBx844upd,ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models,network pruning;unstructured pruning;large language model;ADMM;pre-conditioned conjugate gradient;optimization,5.333333333333333,3.0,Xiang Meng;Kayhan Behdin;Haoyue Wang;Rahul Mazumder,Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology,PhD student;PhD student;PhD student;Associate Professor,https://neurips.cc/virtual/2024/poster/96911,,,https://openreview.net/forum?id=0lBx844upd,/media/PosterPDFs/NeurIPS%202024/96911.png?t=1731079283.0533488
3,63,-0.07022652,-0.30347943,3,-0.15754262445286776,-0.27458739670972204,"[0.17501033967333007, 0.001086018531578065, 5.709956112739689e-23, 0.8238964274751884, 7.214319903266898e-06]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,0lau89u4oE,Accelerating Non-Maximum Suppression: A Graph Theory Perspective,non-maximum suppression;object detection;graph theory,5.5,3.25,King-Siong Si;Lu Sun;Weizhan Zhang;Tieliang Gong;Jiahao Wang;Jiang Liu;Hao Sun,Xi'an Jiaotong University;Xi'an Jiaotong University;North China University of Technology;China Telecom Corporation Ltd. Data&AI Technology Company,MS student;MS student;MS student;Researcher,https://neurips.cc/virtual/2024/poster/96910,,,https://openreview.net/forum?id=0lau89u4oE,/media/PosterPDFs/NeurIPS%202024/96910.png?t=1733315333.5240822
3,64,-0.08510746,-0.26066056,3,-0.15754262445286776,-0.27458739670972204,"[0.1879316275242005, 0.00027676662298158907, 6.05668773546906e-20, 0.8116595556972941, 0.0001320501555238802]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,0m19blQT6y,BitsFusion: 1.99 bits Weight Quantization of Diffusion Model,Diffusion;Quantization;Stable Diffusion;Low bit,5.75,4.5,Yang Sui;Yanyu Li;Anil Kag;Yerlan Idelbayev;Junli Cao;Ju Hu;Dhritiman Sagar;Bo Yuan;Sergey Tulyakov;Jian Ren,Rutgers University;Northeastern University;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Rutgers University;Snap Inc.;Snap Inc.,PhD student;PhD student;Researcher;Researcher;Researcher;Researcher;Researcher;Assistant Professor;Director of Research;Research Scientist,https://neurips.cc/virtual/2024/poster/96909,,,https://openreview.net/forum?id=0m19blQT6y,/media/PosterPDFs/NeurIPS%202024/96909.png?t=1729915675.3170154
3,65,-0.00251228,0.3769304,2,-0.09756174176246091,0.3315038065244718,"[0.003151080835860822, 5.545698811434239e-18, 0.9968461639990911, 4.797446388314281e-11, 2.7551170735963676e-06]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,0mRouJElbZ,ProgressGym: Alignment with a Millennium of Moral Progress,Progress Alignment;AI Alignment;Large Language Models,7.666666666666667,2.6666666666666665,Tianyi Qiu;Yang Zhang;Xuchuan Huang;Jasmine Xinze Li;Jiaming Ji;Yaodong Yang,"University of California, Berkeley;Peking University;Peking University;Peking University;Peking University;Peking University",Intern;Undergrad student;Undergrad student;Intern;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/97875,,,,/media/PosterPDFs/NeurIPS%202024/97875.png?t=1731742041.9348912
3,66,0.42614552,0.08994585,1,0.4047695836386393,-0.0824818227172337,"[0.02080394546657478, 0.9791958905553952, 2.3827443979946277e-11, 1.6395418208960562e-07, 2.0582418433913486e-14]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0nSY8NiILP,Tight Bounds for Learning RUMs from Small Slates,discrete choice;random utility model;approximation theory,6.0,2.75,Flavio Chierichetti;Mirko Giacchini;Ravi Kumar;Alessandro Panconesi;Andrew Tomkins,Sapienza University of Rome;Sapienza University of Rome;Google;Sapienza University of Rome;Google,Full Professor;PhD student;Research Scientist;Full Professor;Researcher,https://neurips.cc/virtual/2024/poster/96908,,,https://openreview.net/forum?id=0nSY8NiILP,/media/PosterPDFs/NeurIPS%202024/96908.png?t=1732698791.0319488
3,67,0.25132486,-0.20319358,1,0.4047695836386393,-0.0824818227172337,"[0.029241111172233374, 0.9701305703030096, 1.5709380377843307e-23, 0.0006283185215394848, 3.2173467315697786e-12]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0nzKznCjFG,Private and Personalized Frequency Estimation in a Federated Setting,federated learning;personalization;privacy,5.75,3.0,Amrith Setlur;Vitaly Feldman;Kunal Talwar,Carnegie Mellon University;Apple AI Research;Apple,PhD student;Research Scientist;Research Scientist,https://neurips.cc/virtual/2024/poster/96907,,,https://openreview.net/forum?id=0nzKznCjFG,
3,68,-0.18157998,0.03947093,4,-0.20782917179182095,0.0014387222347446277,"[0.01256391262329048, 2.9395434385596436e-12, 6.011398943005427e-05, 0.0006309544777133185, 0.9867450189066265]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0o7Rd5jngV,Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling,Transformer;expressive power;theoretical insights,6.333333333333333,3.0,Mingze Wang;Weinan E,Peking University;Peking University,PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96906,,,https://openreview.net/forum?id=0o7Rd5jngV,
3,69,-0.12251995,-0.049827244,4,-0.20782917179182095,0.0014387222347446277,"[0.20235007818868092, 5.327263799076361e-08, 2.8819559120245344e-08, 0.053978426673800976, 0.743671413045321]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0o9E8AsFgW,DarkSAM: Fooling Segment Anything Model to Segment Nothing,Segment Anything Model;Adversarial Example,6.333333333333333,4.0,Ziqi Zhou;Yufei Song;Minghui Li;Shengshan Hu;Xianlong Wang;Leo Yu Zhang;Dezhong Yao;Hai Jin,Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Griffith University;Huazhong University of Science and Technology;Huazhong University of Science and Technology,PhD student;PhD student;Assistant Professor;Associate Professor;PhD student;Researcher;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96905,,,https://openreview.net/forum?id=0o9E8AsFgW,
3,70,-0.18423451,0.25213403,2,-0.09756174176246091,0.3315038065244718,"[0.0006136935697373028, 1.9869975834624754e-19, 0.9907299089236705, 1.460915444626005e-08, 0.008656382897437826]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,0oUutV92YF,ProtGO: Function-Guided Protein Modeling for Unified Representation Learning,Teacher-student;Knowledge Distillation;Protein Function,5.666666666666667,3.6666666666666665,Bozhen Hu;Cheng Tan;Yongjie Xu;Zhangyang Gao;Jun Xia;Lirong Wu;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University;Westlake University, China;Westlake University, China;Westlake University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96904,,,https://openreview.net/forum?id=0oUutV92YF,/media/PosterPDFs/NeurIPS%202024/96904.png?t=1730386167.5899446
3,71,-0.04843812,0.4040603,2,-0.09756174176246091,0.3315038065244718,"[0.0006010037952120888, 7.741499598229475e-21, 0.9993980154656974, 3.3514149891849352e-12, 9.807357388365617e-07]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,0og7nmvDbe,Confidence Regulation Neurons in Language Models,LLMs;Interpretability;Mechanistic Interpretability,7.0,3.75,Alessandro Stolfo;Ben Peng Wu;Wes Gurnee;Yonatan Belinkov;Xingyi Song;Mrinmaya Sachan;Neel Nanda,"ETHZ - ETH Zurich;University of Sheffield;Massachusetts Institute of Technology;Technion, Technion;University of Sheffield;Google DeepMind;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Assistant Professor;Lecturer;Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96903,,,https://openreview.net/forum?id=0og7nmvDbe,
3,72,0.25011468,-0.18353273,1,0.4047695836386393,-0.0824818227172337,"[0.04033993829485361, 0.9589333070535917, 3.415199872872532e-22, 0.0007267546400813724, 1.1473213653206749e-11]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0qb8KoPsej,Accelerating Matroid Optimization through Fast Imprecise Oracles,matroid optimization;weak-strong models;learning-augmented algorithms;algorithms with predictions;query minimization;robustness,5.5,2.75,Franziska Eberle;Felix Hommelsheim;Alexander Lindermayr;Zhenwei Liu;Nicole Megow;Jens Schlöter,Technische Universität Berlin;Universität Bremen;Universität Bremen;Universität Bremen;Universität Bremen,Postdoc;Postdoc;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96902,,,https://openreview.net/forum?id=0qb8KoPsej,
3,73,0.24778247,-0.18444899,1,0.4047695836386393,-0.0824818227172337,"[0.04293298005659663, 0.9562581610251377, 3.4964516155883163e-22, 0.000808858904543991, 1.3721578025993136e-11]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0rl5vWOzRU,Score-Optimal Diffusion Schedules,Diffusion model;adaptive schedule;Annealed Langevin,6.0,3.0,Christopher Williams;Andrew Campbell;Arnaud Doucet;Saifuddin Syed,University of Oxford;University of Oxford;University of Oxford;University of Oxford,PhD student;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96901,,,https://openreview.net/forum?id=0rl5vWOzRU,
3,74,-0.17648138,-0.41862112,3,-0.15754262445286776,-0.27458739670972204,"[0.03776828457429284, 8.860411082334835e-05, 4.4021992156232156e-29, 0.9621430154455637, 9.586931998510037e-08]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,0sJBW05a2W,3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration,Point Cloud Registration;Focus and Matching,5.666666666666667,4.333333333333333,Liyuan Zhang;Le Hui;qi liu;Bo Li;Yuchao Dai,Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwestern Polytechnical University Xi'an;Northwestern Polytechnical University,MS student;Associate Professor;Researcher;Associate Professor;Professor,https://neurips.cc/virtual/2024/poster/96900,,,https://openreview.net/forum?id=0sJBW05a2W,/media/PosterPDFs/NeurIPS%202024/96900.png?t=1731333373.8074756
3,75,-0.16704087,-0.3598848,3,-0.15754262445286776,-0.27458739670972204,"[0.04369102658326468, 4.659178271591918e-05, 3.9525592095901024e-25, 0.9562589120173535, 3.469616666121935e-06]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,0sycTGl4In,4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization,Dynamic Novel View Synthesis;4D Gaussian splatting;Sparse reconstruction;in-the-wild,5.333333333333333,4.666666666666667,Mijeong Kim;Jongwoo Lim;Bohyung Han,Seoul National University;Seoul National University,Full Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96899,,,https://openreview.net/forum?id=0sycTGl4In,/media/PosterPDFs/NeurIPS%202024/96899.png?t=1733712090.5881364
3,76,0.61073065,0.018717432,1,0.4047695836386393,-0.0824818227172337,"[1.4402816251125145e-06, 0.9999985597143625, 2.4391195742619137e-20, 4.0123526107364734e-12, 8.710538894167078e-26]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,0uGlKYS7a2,Maximizing utility in multi-agent environments by anticipating the behavior of other learners,Game Theory; no regret; learning theory;,5.5,3.25,Angelos Assos;Yuval Dagan;Constantinos Costis Daskalakis,Massachusetts Institute of Technology;Massachusetts Institute of Technology,MS student;Full Professor,https://neurips.cc/virtual/2024/poster/96898,,,https://openreview.net/forum?id=0uGlKYS7a2,/media/PosterPDFs/NeurIPS%202024/96898.png?t=1731753379.9098587
3,77,-0.07488669,0.3827278,2,-0.09756174176246091,0.3315038065244718,"[0.0004246310729297866, 5.489983056453771e-21, 0.9995713452841828, 8.80292490506449e-12, 4.02363408458256e-06]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,0uXtFk5KNJ,BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models,block coordinate descent;large language models,5.25,3.75,Qijun Luo;Hengxu Yu;Xiao Li,"The Chinese University of Hong Kong, Shenzhen;The Chinese University of Hong Kong, Shenzhen;Chinese University of Hong Kong Shen Zhen",PhD student;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96897,,,https://openreview.net/forum?id=0uXtFk5KNJ,/media/PosterPDFs/NeurIPS%202024/96897.png?t=1733743857.9232197
3,78,0.022653038,0.24370801,2,-0.09756174176246091,0.3315038065244718,"[0.37984274046234867, 2.377571123047137e-11, 0.6152305871196606, 1.9558984571204413e-06, 0.004924716495757971]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,0zFVhMBZHJ,Mixture of Tokens: Continuous MoE through Cross-Example Aggregation,LLM;Mixture of Experts;MoE;conditional computation;fully-differentiable;language modeling,6.0,3.6666666666666665,Szymon Antoniak;Michał Krutul;Maciej Pióro;Jakub Krajewski;Jan Ludziejewski;Kamil Ciebiera;Krystian Król;Tomasz Odrzygóźdź;Marek Cygan;Sebastian Jaszczur,IDEAS NCBR Sp.;IDEAS NCBR Sp.;University of Warsaw;University of Warsaw;IDEAS NCBR Sp.;University of Warsaw;IDEAS NCBR;Nomagic;University of Warsaw,PhD student;Researcher;PhD student;PhD student;Intern;MS student;Postdoc;Founder / CTO;PhD student,https://neurips.cc/virtual/2024/poster/96896,,,https://openreview.net/forum?id=0zFVhMBZHJ,/media/PosterPDFs/NeurIPS%202024/96896.png?t=1730308223.324062
3,79,0.24368975,0.18879418,0,0.06424707811349922,-0.010531989839880426,"[0.9996471797579501, 0.00015572854073834158, 0.00019303643528975842, 3.7721209354566144e-06, 2.831450863924526e-07]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,0zWzJj6lO3,Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents,cooperative AI;AI safety;LLM agents;cognitive science;language model evaluation;dynamic evaluation;alignment;agency;evolving benchmarks;multi-agent interactions,5.75,3.5,Giorgio Piatti;Zhijing Jin;Max Kleiman-Weiner;Bernhard Schölkopf;Mrinmaya Sachan;Rada Mihalcea,Common Sense Machines;University of Michigan;Swiss Federal Institute of Technology,Principal Researcher;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96895,,,https://openreview.net/forum?id=0zWzJj6lO3,
3,80,-0.16938657,-0.05973538,4,-0.20782917179182095,0.0014387222347446277,"[0.06058422624131105, 3.3347357793816157e-09, 2.4668870875169753e-08, 0.03408390260166007, 0.9053318431534224]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,0zfUiSX5si,AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases,De Novo Peptide sequencing;Proteomics;Mass Spectrum,5.333333333333333,3.0,Jun Xia;Shaorong Chen;Jingbo Zhou;Xiaojun Shan;Wenjie Du;Zhangyang Gao;Cheng Tan;Bozhen Hu;Jiangbin Zheng;Stan Z. Li,"Westlake University, China;Westlake University;Jilin University;University of Electronic Science and Technology of China;University of Science and Technology of China;Westlake University, China;Zhejiang University & Westlake University;Westlake University;Westlake University;Westlake University",PhD student;PhD student;Undergrad student;Undergrad student;Assistant Professor;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96894,,,https://openreview.net/forum?id=0zfUiSX5si,
3,81,-0.25151917,-0.28693447,3,-0.15754262445286776,-0.27458739670972204,"[0.021591239159444255, 2.6974953390528286e-07, 8.704422576112e-19, 0.9768553844618663, 0.0015531066291555363]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,105ZuvpdyW,SegVol: Universal and Interactive Volumetric Medical Image Segmentation,Volumetric Medical Image Segmentation;3D Segmentation Foundation Model;Universal and Interactive 3D Segmentation,7.666666666666667,4.333333333333333,Yuxin Du;Fan BAI;Tiejun Huang;Bo Zhao,Beijing Academy of Artificial Intelligence;The Chinese University of Hong Kong;Peking University;BAAI,Intern;PhD student;Full Professor;Principal Researcher,https://neurips.cc/virtual/2024/poster/96893,,,https://openreview.net/forum?id=105ZuvpdyW,/media/PosterPDFs/NeurIPS%202024/96893.png?t=1731410503.871179
3,82,0.04577409,-0.24324691,0,0.06424707811349922,-0.010531989839880426,"[0.5897629860233415, 0.04369758017571073, 5.087780480051057e-21, 0.36653735083511363, 2.0829658341300515e-06]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,1067784F6e,Data Distribution Valuation,Data distribution valuation;Huber model;Maximum mean discrepancy,6.333333333333333,4.333333333333333,Xinyi Xu;Shuaiqi Wang;Chuan-Sheng Foo;Bryan Kian Hsiang Low;Giulia Fanti,"National University of Singapore;Carnegie Mellon University;Institute for Infocomm Research, A*STAR;National University of Singapore;Carnegie Mellon University",PhD student;PhD student;Principal Scientist;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96892,,,https://openreview.net/forum?id=1067784F6e,/media/PosterPDFs/NeurIPS%202024/96892.png?t=1731176029.7581189
3,83,-0.22563006,-0.049784996,4,-0.20782917179182095,0.0014387222347446277,"[0.010094559017150277, 3.077892949776133e-11, 1.3302856846075674e-07, 0.008310252995567896, 0.9815950549279344]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,12A1RT1L87,Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?,Dataset Condensation;Dataset Distillation,5.666666666666667,3.6666666666666665,Lingao Xiao;Yang He,"School of Computer Science and  Engineering, Nanyang Technological University;Institute of High Performance Computing, Singapore, A*STAR",Undergrad student;Researcher,https://neurips.cc/virtual/2024/poster/96891,,,https://openreview.net/forum?id=12A1RT1L87,/media/PosterPDFs/NeurIPS%202024/96891.png?t=1731138766.8349779
3,84,-0.20074943,0.040258985,4,-0.20782917179182095,0.0014387222347446277,"[0.007200327850317924, 6.502165712791681e-13, 8.10857512124621e-05, 0.0004286408868540623, 0.9922899455109653]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,135eKqDoRR,Bayesian-guided Label Mapping for Visual Reprogramming,visual reprogramming;adversarial reprogramming;output label mapping;Bayesian probability,7.25,4.0,Chengyi Cai;Zesheng Ye;Lei Feng;Jianzhong Qi;Feng Liu,University of Melbourne;Singapore University of Technology and Design;University of Melbourne;University of Melbourne,PhD student;Assistant Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96890,,,https://openreview.net/forum?id=135eKqDoRR,
3,85,-0.1496939,0.30529067,2,-0.09756174176246091,0.3315038065244718,"[0.00030553723237562513, 1.5141566617063966e-20, 0.9992812858134419, 5.047668929540751e-10, 0.00041317644941548125]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,14hLJr6kZ3,Enhancing Domain Adaptation through Prompt Gradient Alignment,transfer learning; domain adaptation; prompt-tuning,6.25,3.25,Hoang Phan;Tung Lam Tran;Quyen Tran;Trung Le,VinAi Research;VinAI Research;Monash University;New York University,Research resident;Research Resident;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96889,,,https://openreview.net/forum?id=14hLJr6kZ3,/media/PosterPDFs/NeurIPS%202024/96889.png?t=1732036918.0147438
3,86,0.2630342,0.051892787,0,0.06424707811349922,-0.010531989839880426,"[0.9049245023246221, 0.09489445941341441, 2.240682219184142e-09, 0.00018097405910800043, 6.196217335887093e-08]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,15460JjocO,Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners,multi-agent;reinforcement learning;robustness;diversity;specialization,7.0,3.6666666666666665,Rujikorn Charakorn;Poramate Manoonpong;Nat Dilokthanakul,Sakana AI;Vidyasirimedhi Institute of Science and Technology;King Mongkut's Institute of Technology Ladkrabang,Intern;Full Professor;Lecturer,https://neurips.cc/virtual/2024/poster/96888,,,https://openreview.net/forum?id=15460JjocO,/media/PosterPDFs/NeurIPS%202024/96888.png?t=1731395258.7214391
3,87,0.61719507,-0.024593957,1,0.4047695836386393,-0.0824818227172337,"[6.039491606566953e-07, 0.9999993960473037, 6.484140035665212e-23, 3.5357081564332076e-12, 7.202656362718314e-27]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,15Jm9v7wCo,No-Regret Learning for Fair Multi-Agent Social Welfare Optimization,Online Learning;Nash Social Welfare,5.666666666666667,3.3333333333333335,Mengxiao Zhang;Ramiro Deo-Campo Vuong;Haipeng Luo,University of Southern California;University of Southern California,Undergrad student;Associate Professor,https://neurips.cc/virtual/2024/poster/96887,,,https://openreview.net/forum?id=15Jm9v7wCo,
3,88,-0.14552048,-0.15470643,3,-0.15754262445286776,-0.27458739670972204,"[0.2410744782307115, 1.6531532477454993e-06, 1.1417859719014447e-12, 0.628118179409655, 0.1308056892052441]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,15PS30UOUp,Kuro Siwo: 33 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping,Synthetic Aperture Radar;SAR;Deep Learning;Remote Sensing;Floods;dataset,6.75,3.75,Nikolaos Ioannis Bountos;Maria Sdraka;Angelos Zavras;Andreas Karavias;Ilektra Karasante;Themistocles Herekakis;Angeliki Thanasou;Dimitrios Michail;Ioannis Papoutsis,National Observatory of Athens;National Observatory of Athens;Harokopio University;The Centre for Research & Technology;National Observatory of Athens ;National Observatoty of Athens;National Observatory of Athens;Harokopio University;National Technical University of Athens,PhD student;Researcher;PhD student;Researcher;Researcher;Researcher;Researcher;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97874,,,,
3,89,0.004352061,-0.07103703,0,0.06424707811349922,-0.010531989839880426,"[0.9037619662032781, 0.00011345421647380141, 7.929058038643269e-11, 0.08440627284763749, 0.011718306653320125]","[0.012507893888733275, 0.020993339561298993]",0.24101009226576836,164QnJsYjF,Dense Associative Memory Through the Lens of Random Features,Associative Memory;Kernels;Random Features;Hopfield Network,6.0,3.0,Benjamin Hoover;Duen Horng Chau;Hendrik Strobelt;Parikshit Ram;Dmitry Krotov,International Business Machines;International Business Machines;International Business Machines;Massachusetts Institute of Technology;Georgia Institute of Technology,AI Research Engineer;Principal Researcher;Principal Researcher;Researcher;Full Professor,https://neurips.cc/virtual/2024/poster/96886,,,https://openreview.net/forum?id=164QnJsYjF,/media/PosterPDFs/NeurIPS%202024/96886.png?t=1733846086.053208
3,90,-0.31772932,0.41427824,2,-0.09756174176246091,0.3315038065244718,"[2.1649036400779403e-07, 3.6458964964760254e-32, 0.9999996296593763, 4.6533034689450345e-15, 1.5385025505793458e-07]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,168NLzTpw8,Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation,Vision-Language;Region-Level Understanding;Multimodal Large Language Model,5.75,3.75,Yaoyuan Liang;Zhuojun Cai;Jian Xu;Guanbo Huang;Yiran Wang;Xiao Liang;Jiahao Liu;Ziran Li;Jingang Wang;Shao-Lun Huang,"Tsinghua Shenzhen International Graduate School, Tsinghua University;Microsoft;University of Electronic Science and Technology of China;Tsinghua University;Tsinghua University;Meituan;Meituan;Tsinghua University",PhD student;Intern;Undergrad student;MS student;MS student;Researcher;Researcher;Associate Professor,https://neurips.cc/virtual/2024/poster/96885,,,https://openreview.net/forum?id=168NLzTpw8,
3,91,-0.118134014,0.26676714,2,-0.09756174176246091,0.3315038065244718,"[0.003110297892057982, 1.5626334327752127e-17, 0.9922988857068731, 2.2334576636119445e-08, 0.00459079406649247]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,181llen2gw,A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks,Vision-Language Model;Fairness;Debias,6.333333333333333,3.6666666666666665,Hoin Jung;Taeuk Jang;Xiaoqian Wang,Purdue University;Purdue University;Purdue University,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96884,,,https://openreview.net/forum?id=181llen2gw,/media/PosterPDFs/NeurIPS%202024/96884.png?t=1731379505.2628894
3,92,-0.19037005,0.30377576,2,-0.09756174176246091,0.3315038065244718,"[8.640569846944161e-05, 4.295679833929107e-22, 0.9995496690989757, 2.1219440165678548e-10, 0.0003639249903605009]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,18FGRNd0wZ,Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation,tokenization of crystals;language models;materials generation,6.0,3.5,Keqiang Yan;Xiner Li;Hongyi Ling;Kenna Ashen;Carl Edwards;Raymundo Arroyave;Marinka Zitnik;Heng Ji;Xiaofeng Qian;Xiaoning Qian;Shuiwang Ji,"Texas A&M University;Texas A&M University - College Station;Texas A&M University - College Station;Texas A&M University - College Station;Genentech;Texas A&M University Main Campus;Harvard University;University of Illinois, Urbana-Champaign;Texas A&M University;Texas A&M;Texas A&M University",PhD student;PhD student;PhD student;PhD student;Intern;Assistant Professor;Full Professor;Associate Professor;Full Professor;Professor,https://neurips.cc/virtual/2024/poster/96883,,,https://openreview.net/forum?id=18FGRNd0wZ,/media/PosterPDFs/NeurIPS%202024/96883.png?t=1733428872.6393995
3,93,-0.18803668,0.09546091,4,-0.20782917179182095,0.0014387222347446277,"[0.00919918900849636, 6.695284497100583e-14, 0.0036371498002826254, 8.726816688618902e-05, 0.9870763930242679]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,18RdkSv9h9,FINALLY: fast and universal speech enhancement with studio-like quality,speech enhancement; generative models,6.5,4.75,Nicholas Babaev;Kirill Tamogashev;Azat Saginbaev;Ivan Shchekotov;Hanbin Bae;Hosang Sung;WonJun Lee;Hoon-Young Cho;Pavel Andreev,"Samsung;Skolkovo Institute of Science and Technology;Moscow Institute of Physics and Technology;Samsung;Samsung;Samsung;Higher School of Economics, Higher School of Economics",Researcher;MS student;MS student;Principal Researcher;Researcher;Vice President;MS student,https://neurips.cc/virtual/2024/poster/96882,,,https://openreview.net/forum?id=18RdkSv9h9,/media/PosterPDFs/NeurIPS%202024/96882.png?t=1731683595.700073
3,94,0.32727078,-0.11709024,1,0.4047695836386393,-0.0824818227172337,"[0.00829024991911873, 0.9916892858649579, 2.9201093844536554e-20, 2.046421577665381e-05, 1.466746265696637e-13]","[0.016085080419131634, 0.012246207953017759]",0.18521536717731285,1ATLLgvURu,Learning-Augmented Priority Queues,learning-augmented algorithms;algorithms with predictions;priority queue;shortest paths;Dijkstra,5.75,4.25,Ziyad Benomar;Christian Coester,University of Oxford,Associate Professor,https://neurips.cc/virtual/2024/poster/96881,,,https://openreview.net/forum?id=1ATLLgvURu,
3,95,0.3095995,0.5030761,2,-0.09756174176246091,0.3315038065244718,"[0.15943356801920666, 1.1979772010779869e-11, 0.8405664319685454, 1.7565339808592202e-13, 9.263110074759286e-14]","[0.01781759048224023, 0.005368401719956655]",0.1871405884305889,1BZKqZphsW,Risk-Averse Fine-tuning of Large Language Models,Risk Averse Reinforcement Learning;Large Language Model Finetuning,5.8,3.2,Sapana Chaudhary;Ujwal Dinesha;Dileep Kalathil;Srinivas Shakkottai,Texas A&M University;Texas A&M University - College Station;Texas A&M University;Texas A&M,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96880,,,https://openreview.net/forum?id=1BZKqZphsW,/media/PosterPDFs/NeurIPS%202024/96880.png?t=1733328781.5713553
3,96,-0.26364937,-0.38828564,3,-0.15754262445286776,-0.27458739670972204,"[0.01182849916292994, 1.4311377368865814e-06, 2.6633692847504833e-25, 0.9881660069545469, 4.062744786213223e-06]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,1CssOqRYyz,Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds,compression;point cloud;diffusion,4.0,4.0,Kai Liu;Kang You;Pan Gao,"Nanjing University of Aeronautics and Astronautics;Nanjing university;Nanjing University of Aeronautics and Astronautics, Tsinghua University",MS student;PhD student;Associate Professor,,,,,
3,97,-0.25224024,-0.31188005,3,-0.15754262445286776,-0.27458739670972204,"[0.018046255767697226, 4.5389746436366986e-07, 2.2094607459719938e-20, 0.9815831185862631, 0.0003701717485752238]","[0.01070519464384802, 0.00918874437220547]",0.16222690658047886,1Du3mMP5YN,Learning to Shape In-distribution Feature Space for Out-of-distribution Detection,Out-of-distribution Detection,5.75,4.0,Yonggang Zhang;Jie Lu;Bo Peng;Zhen Fang;Yiu-ming Cheung,Hong Kong Baptist University;University of Technology Sydney;University of Technology Sydney,Postdoc;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96879,,,https://openreview.net/forum?id=1Du3mMP5YN,/media/PosterPDFs/NeurIPS%202024/96879.png?t=1731745181.7993424
3,98,-0.30068702,-0.14781809,4,-0.20782917179182095,0.0014387222347446277,"[0.012578199726448906, 1.5550032268885714e-10, 2.4361003445414424e-10, 0.17239902038336616, 0.8150227794910745]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,1ELFGSNBGC,Multiview Scene Graph,scene representation; spatial understanding; place recognition; object correspondence; scene graph,5.25,3.25,Juexiao Zhang;Gao Zhu;Sihang Li;Xinhao Liu;Haorui Song;Xinran Tang;Chen Feng,New York University;New York University;New York University;New York University;New York University;New York University;New York University,PhD student;MS student;PhD student;PhD student;MS student;MS student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96878,,,https://openreview.net/forum?id=1ELFGSNBGC,/media/PosterPDFs/NeurIPS%202024/96878.png?t=1731728482.5838113
3,99,-0.09486352,0.005280091,4,-0.20782917179182095,0.0014387222347446277,"[0.2375538836032225, 1.7251696220656927e-08, 1.8942078800305122e-06, 0.012199817342672488, 0.7502443875945289]","[0.005983344919043205, 0.005486799171021812]",0.22440704554585097,1F32iCJFfa,Schrodinger Bridge Flow for Unpaired Data Translation,unpaired data translation;diffusion models;Schrodinger bridge;bridge matching;stochastic interpolant;flow matching,6.5,4.0,Valentin De Bortoli;Iryna Korshunova;Andriy Mnih;Arnaud Doucet,University of Oxford;Google DeepMind;Google DeepMind;University of Oxford,Postdoc;Researcher;Research Scientist;Full Professor,https://neurips.cc/virtual/2024/poster/96877,,,https://openreview.net/forum?id=1F32iCJFfa,/media/PosterPDFs/NeurIPS%202024/96877.png?t=1731688420.732189
4,0,0.08799766,-0.06060414,0,0.03540969834964841,0.014433900922561742,"[0.8528656012116412, 0.0030830744102173808, 2.9237423545097405e-11, 0.1440485685029598, 2.755845944117377e-06]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,00Sx577BT3,The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning,numerical simulations;fluid-dynamics;partial differential equations;operator learning,6.666666666666667,3.6666666666666665,Ruben Ohana;Michael McCabe;Lucas Thibaut Meyer;Rudy Morel;Fruzsina Julia Agocs;Miguel Beneitez;Marsha Berger;Blakesley Burkhart;Stuart B. Dalziel;Drummond Buschman Fielding;Daniel Fortunato;Jared A. Goldberg;Keiya Hirashima;Yan-Fei Jiang;Rich Kerswell;Suryanarayana Maddu;Jonah M. Miller;Payel Mukhopadhyay;Stefan S. Nixon;Jeff Shen;Romain Watteaux;Bruno Régaldo-Saint Blancard;François Rozet;Liam Holden Parker;Miles Cranmer;Shirley Ho,"Flatiron Institute;University of Colorado, Boulder;INRIA;Flatiron Institute;Flatiron Institute;University of Cambridge;Flatiron Institute;Rutgers University;University of Cambridge;Simons Foundation;Flatiron Institute;Flatiron Institute;Simons Foundation;University of Cambridge;Flatiron Institute/Simons Foundation;Los Alamos National Laboratory;University of California, Berkeley;University of Cambridge;Princeton University;CEA;Flatiron Institute;Flatiron Institute;Flatiron Institute;University of Cambridge;Carnegie Mellon University;The University of Tokyo",Postdoc;PhD student;PhD student;Postdoc;Postdoc;Postdoc;Full Professor;Assistant Professor;Director of the GK Batchelor Laboratory;Postdoc;Researcher;Postdoc;Researcher;Full Professor;Postdoc;Researcher;Postdoc;PhD student;PhD student;Researcher;Postdoc;Intern;Researcher;Assistant Professor;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/97882,,,,
4,1,-0.08406016,0.2851326,2,-0.09305589277997829,0.3321079419566604,"[0.0014236765683900154, 2.963170733292754e-17, 0.9970404781808943, 1.5591093533906377e-10, 0.0015358450948044823]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,00uVk06eVK,On the Noise Robustness of In-Context Learning for Text Generation,In-Context Learning;Large Language Models;Noise Robustness,6.333333333333333,3.0,Hongfu Gao;Feipeng Zhang;Wenyu Jiang;Jun Shu;Feng Zheng;Hongxin Wei,Xi'an Jiaotong University;Xi'an Jiaotong University;Nanjing University;Xi'an Jiaotong University;Southern University of Science and Technology;Southern University of Science and Technology,MS student;Full Professor;PhD student;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96962,,,https://openreview.net/forum?id=00uVk06eVK,/media/PosterPDFs/NeurIPS%202024/96962.png?t=1731587881.4159098
4,2,-0.16364236,-0.11411294,0,0.03540969834964841,0.014433900922561742,"[0.4862652003256604, 9.623797011183956e-08, 3.1821107311170653e-10, 0.14338784629234025, 0.37034685682581814]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,01I55gys19,Few-Class Arena: A Benchmark for Efficient Vision Model Selection and Dataset Difficulty,few-class;efficiency;neural network;convolutional neural network;transformer;dataset difficulty measurement;scaling law,5.0,3.3333333333333335,Bryan Bo Cao;Lawrence O'Gorman;Michael Coss;Shubham Jain,Nokia networks GmbH;State University of New York at Stony Brook,Intern;Assistant Professor,,,,,
4,3,0.07371062,-0.27021888,3,-0.11151072469142234,-0.26545137332798735,"[0.017303849698992294, 0.11386406288347872, 9.000675666030012e-23, 0.8688320870377956, 3.7973345212092956e-10]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,01XV5Za56k,Testing Calibration in Nearly-Linear Time,Calibration;Property testing;Linear programming,6.25,3.25,Lunjia Hu;Arun Jambulapati;Kevin Tian;Chutong Yang,Stanford University;Stanford University;Stanford University;University of Texas at Austin,PhD student;PhD student;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96961,,,https://openreview.net/forum?id=01XV5Za56k,
4,4,-0.1284643,0.3103237,2,-0.09305589277997829,0.3321079419566604,"[0.0001134894808775128, 3.8390025313024464e-20, 0.9993399682264605, 2.939719439055898e-12, 0.0005465422897221336]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,01lhHg8H9p,GLBench: A Comprehensive Benchmark for Graph with Large Language Models,Graph learning;Large Language Model;Zero-Shot,6.75,4.0,Yuhan Li;Peisong Wang;Xiao Zhu;Aochuan Chen;Haiyun Jiang;Deng Cai;Victor Wai Kin Chan;Jia Li,"Hong Kong University of Science and Technology;Tsinghua University;Beijing University of Posts and Telecommunications;Hong Kong University of Science and Technology;Tencent AI Lab;Tencent AI Lab;Shenzhen International Graduate School, Tsinghua University;Hong Kong University of Science and Technology",PhD student;MS student;Undergrad student;PhD student;Researcher;Research Scientist;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97881,,,,/media/PosterPDFs/NeurIPS%202024/97881.png?t=1731478194.2539835
4,5,-0.23808402,0.26056772,2,-0.09305589277997829,0.3321079419566604,"[4.74151276692285e-05, 3.174150573608721e-22, 0.9951245961500834, 6.207336261343429e-12, 0.004827988716040253]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,01qa1ZJs65,Bridge the Modality and Capability Gaps in Vision-Language Model Selection,Vision-Language Model;Model Selection;Zero-Shot Image Classification,5.25,4.0,Chao Yi;Yuhang He;De-Chuan Zhan;Han-Jia Ye,Nanjing University;Nanjing University;Nanjing University;Nanjing University,MS student;Undergrad student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96960,,,https://openreview.net/forum?id=01qa1ZJs65,/media/PosterPDFs/NeurIPS%202024/96960.png?t=1731123927.9174762
4,6,-0.10493148,-0.30384988,3,-0.11151072469142234,-0.26545137332798735,"[0.016477180849620868, 0.0001993624419720767, 6.341049137785144e-22, 0.9833187402478609, 4.716460546263369e-06]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,01s5ODIHKd,FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space,deep watermarking;latent frequency optimization,5.5,3.75,YiYang Guo;Ruizhe Li;Mude Hui;Hanzhong Allan Guo;Chen Zhang;Chuangjian Cai;Le Wan;Shangfei Wang,"University of Science and Technology of China;University of California, Santa Cruz;Renmin University of China;Tsinghua University;University of Science and Technology of China;University of Science and Technology of China",MS student;PhD student;MS student;PhD student;Full Professor;PhD student,https://neurips.cc/virtual/2024/poster/96959,,,https://openreview.net/forum?id=01s5ODIHKd,/media/PosterPDFs/NeurIPS%202024/96959.png?t=1730176108.8718698
4,7,-0.295713,-0.42771262,3,-0.11151072469142234,-0.26545137332798735,"[0.0021290155472389635, 7.151614184431666e-07, 8.18291739831932e-27, 0.9978691022141188, 1.1670772239582266e-06]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,02CIZ8qeDc,PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection,3D anomaly detection;Zero-shot 3D anomaly detection,6.0,3.6666666666666665,Qihang Zhou;Jiangtao Yan;Shibo He;Wenchao Meng;Jiming Chen,Zhejiang University;Zhejiang University;Zhejiang University;Zhejiang University,PhD student;MS student;Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96958,,,https://openreview.net/forum?id=02CIZ8qeDc,/media/PosterPDFs/NeurIPS%202024/96958.png?t=1731476864.9817398
4,8,-0.3188932,-0.023905918,4,-0.22395180066953493,0.001735864936139136,"[0.013212737693285438, 6.182893706651389e-15, 9.718838825466285e-06, 0.00010316753005264641, 0.9866743759378304]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,02HWT9c4Lp,Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion,Semantic Scene completion，Voxel Proposal，Knowledge Distillation,5.5,4.0,Lubo Wang;Di Lin;Kairui Yang;Ruonan Liu;Qing Guo;Wuyuan Xie;Miaohui Wang;Lingyu Liang;Yi Wang;Ping Li,"Tianjin University;Tianjin University;Tianjin University;Tianjin University; Agency for Science, Technology and Research (A*STAR));Department of Software Engineering, Shenzhen University;Shenzhen University;South China University of Technology;Shenzhen University;The Hong Kong Polytechnic University",MS student;Associate Professor;PhD student;Associate Professor;Researcher;Associate Professor;Associate Professor;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96957,,,https://openreview.net/forum?id=02HWT9c4Lp,/media/PosterPDFs/NeurIPS%202024/96957.png?t=1731159292.6143699
4,9,0.52375084,0.03593809,1,0.4053444721989165,-0.08263556956380372,"[0.00015688279399211566, 0.9998328868798358, 2.4558494494059363e-16, 1.0230326171887551e-05, 3.1171519110824877e-30]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,02r24A8doi,Achieving Constant Regret in Linear Markov Decision Processes,Reinforcement learning;Constant regret;Misspecified linear MDP,5.25,2.75,Weitong Zhang;Zhiyuan Fan;Jiafan He;Quanquan Gu,"Massachusetts Institute of Technology;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles",PhD student;PhD student;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96956,,,https://openreview.net/forum?id=02r24A8doi,
4,10,-0.24769914,0.06194072,4,-0.22395180066953493,0.001735864936139136,"[0.010917117599472854, 3.114540820865124e-15, 0.0008145687794478873, 5.283803206489287e-06, 0.9882630298178697]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,04EC4ZnZJj,MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers,transformer architecture;large language model;computational complexity reduction,6.0,3.5,Ning Ding;Yehui Tang;Haochen Qin;Zhenli Zhou;Chao Xu;Lin Li;Kai Han;Liao Heng;Yunhe Wang,"Peking University;Huawei Technologies Ltd.;Huawei Technologies Ltd.;Peking University;Peking University;Huawei Noah's Ark Lab;, Tsinghua University;Huawei Noah's Ark Lab",PhD student;Researcher;Researcher;MS student;Full Professor;Principal Researcher;Principal Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96955,,,https://openreview.net/forum?id=04EC4ZnZJj,
4,11,0.45866024,0.07679337,1,0.4053444721989165,-0.08263556956380372,"[0.007416809961368905, 0.9924981812083488, 1.9567782972365268e-12, 8.500882832551134e-05, 3.1356810040751418e-24]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,06JRFVK88O,Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games,Multi-agent Reinforcement Learning;Imitation Learning,6.666666666666667,3.0,The Viet Bui;Tien Anh Mai;Thanh Hong Nguyen,Singapore Management University;University of Oregon;Singapore Management University,Assistant Professor;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96954,,,https://openreview.net/forum?id=06JRFVK88O,/media/PosterPDFs/NeurIPS%202024/96954.png?t=1731744891.8886228
4,12,-0.21952832,-0.2596673,3,-0.11151072469142234,-0.26545137332798735,"[0.0664655359108118, 6.104403258028055e-07, 3.6680371025643657e-17, 0.9287352732051669, 0.0047985804436953714]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,06Vt6f2js7,SyncTweedies: A General Generative Framework Based on Synchronized Diffusions,Diffusion Models;Synchronization;Texturing;3D Gaussian Splatting;Mesh;Panorama,6.666666666666667,3.6666666666666665,Jaihoon Kim;Juil Koo;Kyeongmin Yeo;Minhyuk Sung,KAIST;Adobe Systems;Korea Advanced Institute of Science & Technology;Korea Advanced Institute of Science & Technology,MS student;Intern;Undergrad student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96953,,,https://openreview.net/forum?id=06Vt6f2js7,
4,13,0.5387558,-0.021885695,1,0.4053444721989165,-0.08263556956380372,"[1.492154887078711e-05, 0.9999784450951958, 7.460473303421459e-20, 6.633355933184566e-06, 8.975907033503517e-33]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,07N0qoaZ2L,Improved Analysis for Bandit Learning in Matching Markets,Bandits;Matching markets;Stable matching;Stable regret;Exploration and exploitation;$\alpha$-condition,5.5,3.0,Fang Kong;Zilong Wang;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;John Hopcroft Center, Shanghai Jiao Tong University",PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96952,,,https://openreview.net/forum?id=07N0qoaZ2L,/media/PosterPDFs/NeurIPS%202024/96952.png?t=1731746661.9360106
4,14,-0.31746334,-0.03755091,4,-0.22395180066953493,0.001735864936139136,"[0.016163450446825284, 1.6983681697280374e-14, 3.3802927864252054e-06, 0.00020368965042783595, 0.9836294796099436]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,08A6X7FSTs,Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text,Text-to-3D Scene Generation;Latent Diffusion Models,5.5,4.5,Xinyang Li;Zhangyu Lai;Linning Xu;Yansong Qu;Liujuan Cao;Shengchuan Zhang;Bo Dai;Rongrong Ji,Xiamen University;Xiamen University;Xiamen University;Xiamen University;Xiamen University;Shanghai AI Laboratory;Xiamen University;The Chinese University of Hong Kong,PhD student;MS student;PhD student;Full Professor;Assistant Professor;Scientist;Full Professor;Ph.D. student,https://neurips.cc/virtual/2024/poster/96951,,,https://openreview.net/forum?id=08A6X7FSTs,/media/PosterPDFs/NeurIPS%202024/96951.png?t=1732593534.8700738
4,15,0.21572201,0.15297481,0,0.03540969834964841,0.014433900922561742,"[0.9996174842836404, 0.0001563705139771412, 5.041226683927493e-05, 0.0001757314948553008, 1.4406879236477116e-09]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,08GbdALmEs,Learning Versatile Skills with Curriculum Masking,reinforcement learning;unsupervised pretraining;masked prediction;curriculum learning,5.25,3.25,Yao Tang;Zhihui Xie;Zichuan Lin;Deheng Ye;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;Tencent AI Lab;Tencent;John Hopcroft Center, Shanghai Jiao Tong University",Undergrad student;MS student;Researcher;Principal Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96950,,,https://openreview.net/forum?id=08GbdALmEs,/media/PosterPDFs/NeurIPS%202024/96950.png?t=1733319308.3295946
4,16,-0.17784788,-0.16018736,3,-0.11151072469142234,-0.26545137332798735,"[0.40070866397477256, 3.2657681959943506e-07, 3.6273155995778837e-12, 0.439846282285591, 0.1594447271591895]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,08nbMTxazb,Chicks4FreeID: A Benchmark Dataset for Chicken Re-Identification,animal re-identification;chicken re-identification;chicken dataset;re-identification dataset;benchmark dataset;closed-set re-identification;computer vision;chicken instance segmentation;poultry;livestock,4.75,4.0,Daria Kern;Tobias Schiele;Ulrich Klauck;Winfred Ingabire,Glasgow Caledonian University;Hochschule Aalen;Glasgow Caledonian University,PhD student;Full Professor;Lecturer,,,,,
4,17,0.12485067,-0.17534988,3,-0.11151072469142234,-0.26545137332798735,"[0.12090064645337144, 0.2006931379081869, 8.329797049212649e-18, 0.6784062145216995, 1.1167421211624073e-09]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,08oUnmtj8Q,FSEO: A Few-Shot Evolutionary Optimization Framework for Expensive Multi-Objective Optimization and Constrained Optimization,Expensive optimization;few-shot optimization;multi-objective optimization;constrained optimization;surrogate-assisted evolutionary optimization,4.5,3.5,Xunzhao Yu,,,,,,,
4,18,-0.045080878,-0.32160506,3,-0.11151072469142234,-0.26545137332798735,"[0.009134276142566001, 0.00294041961052778, 4.3509268869801156e-24, 0.9879252377775153, 6.646939097917707e-08]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,09RKw0vXjR,Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations,feature selection;sparse coding;dictionary learning;compressed sensing;iterative hard thresholding;pruning method,5.75,3.0,Yasutoshi Ida;Sekitoshi Kanai;Atsutoshi Kumagai;Tomoharu Iwata;Yasuhiro Fujiwara,NTT;NTT;NTT;NTT;NTT,Researcher;Researcher;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96949,,,https://openreview.net/forum?id=09RKw0vXjR,/media/PosterPDFs/NeurIPS%202024/96949.png?t=1733375377.8112724
4,19,-0.29219365,-0.1354431,4,-0.22395180066953493,0.001735864936139136,"[0.10783101333493512, 7.028867971105435e-11, 7.740051628416918e-10, 0.03605054371257321, 0.8561184421081979]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,09nyBqSdUz,RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance,Consistent image generation;Diverse image generation;Improve temporal-consistency;Feature injection from multiple images,5.5,4.0,Jiaojiao Fan;Haotian Xue;Qinsheng Zhang;Yongxin Chen,Georgia Institute of Technology;Georgia Institute of Technology;Georgia Institute of Technology;NVIDIA,PhD student;PhD student;Associate Professor;Research Intern,https://neurips.cc/virtual/2024/poster/96948,,,https://openreview.net/forum?id=09nyBqSdUz,/media/PosterPDFs/NeurIPS%202024/96948.png?t=1731392354.7708242
4,20,0.22983314,0.005944166,0,0.03540969834964841,0.014433900922561742,"[0.849229462161634, 0.11792801940543662, 2.154223814522335e-10, 0.032842518169561546, 4.794574147611858e-11]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0AumdfLzpK,A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations,Visual Reinforcement Learning;Generalization,6.0,4.0,Wonil Song;Hyesong Choi;Kwanghoon Sohn;Dongbo Min,Yonsei Univ.;Ewha Womans University;Yonsei University;Ewha Womans University,PhD student;PhD student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96947,,,https://openreview.net/forum?id=0AumdfLzpK,/media/PosterPDFs/NeurIPS%202024/96947.png?t=1732451612.1247888
4,21,-0.2313607,0.15489271,4,-0.22395180066953493,0.001735864936139136,"[0.0068566146848841655, 3.081881156352451e-17, 0.2301947682152496, 9.131056926963326e-08, 0.762948525789297]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,0AwMciNShl,"Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality",Human evaluation;text-to-video models,5.25,4.0,Tianle Zhang;Langtian Ma;Yuchen Yan;Yuchen Zhang;Yue Yang;Ziyao Guo;Wenqi Shao;Kai Wang;Yang You;Yu Qiao;Ping Luo;Kaipeng Zhang,University of Electronic Science and Technology of China;Southern University of Science and Technology;The University of Nottingham Ningbo China;University of Electronic Science and Technology of China;Xidian University;Shanghai AI Laboratory;National University of Singapore;National University of Singapore;Shanghai AI Laboratory;The University of Hong Kong;Shanghai Jiaotong University,Undergrad student;Undergrad student;Undergrad student;Undergrad student;MS student;Researcher;PhD student;Professor;Researcher;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96946,,,https://openreview.net/forum?id=0AwMciNShl,/media/PosterPDFs/NeurIPS%202024/96946.png?t=1729079669.652648
4,22,0.44196302,-0.22339565,1,0.4053444721989165,-0.08263556956380372,"[1.103612646651763e-06, 0.9999249009540851, 2.0618331048481032e-29, 7.399543326804264e-05, 1.5578558763551908e-30]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0C3bLHwjsY,Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions,Online Matching;Competitive Analysis;Fairness Maximization,6.25,3.0,Will Ma;Pan Xu,Columbia University;New Jersey Institute of Technology,Assistant Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96945,,,https://openreview.net/forum?id=0C3bLHwjsY,/media/PosterPDFs/NeurIPS%202024/96945.png?t=1731641014.5806563
4,23,0.31953293,-0.23248373,1,0.4053444721989165,-0.08263556956380372,"[5.039686923603606e-05, 0.9973623849736825, 1.1065276449342537e-26, 0.0025872181570816273, 2.739350040022564e-22]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0DE1dLMW2b,Quantum algorithm for large-scale market equilibrium computation,market equilibrium computation;quantum algorithm,6.0,2.75,Po-Wei Huang;Patrick Rebentrost,Centre for Quantum Technologies;National University of Singapore,Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96944,,,https://openreview.net/forum?id=0DE1dLMW2b,/media/PosterPDFs/NeurIPS%202024/96944.png?t=1731426989.5298698
4,24,0.0025802255,-0.08199731,0,0.03540969834964841,0.014433900922561742,"[0.8163513317007373, 0.00013651620615024143, 5.120645627821013e-11, 0.18297153902796068, 0.0005406130139452475]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0EfUYVMrLv,Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment,non-stationary environments;continuous distribution shift;test-time adaptation;unlabeled data,6.666666666666667,4.0,Zhen-Yu Zhang;Zhiyu Xie;Huaxiu Yao;Masashi Sugiyama,"RIKEN;Stanford University;Department of Computer Science, University of North Carolina at Chapel Hill;The University of Tokyo",Postdoc;MS student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96943,,,https://openreview.net/forum?id=0EfUYVMrLv,/media/PosterPDFs/NeurIPS%202024/96943.png?t=1731687693.6296034
4,25,0.023439856,-0.079839304,0,0.03540969834964841,0.014433900922561742,"[0.8126221132808293, 0.0003314863134920946, 3.232319983486897e-11, 0.18689276379711456, 0.0001536365762408509]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0G0VpMjKyV,Sketching for Distributed Deep Learning: A Sharper Analysis,sketching;distributed learning;federated learning;optimization,5.666666666666667,4.0,Mayank Shrivastava;Berivan Isik;Qiaobo Li;Sanmi Koyejo;Arindam Banerjee,"University of Illinois, Urbana Champaign;Stanford University;Department of Computer Science, University of Illinois at Urbana-Champaign;University of Illinois, Urbana Champaign;Google",MS student;PhD student;PhD student;Professor;Research Scientist,https://neurips.cc/virtual/2024/poster/96942,,,https://openreview.net/forum?id=0G0VpMjKyV,/media/PosterPDFs/NeurIPS%202024/96942.png?t=1733481266.9121125
4,26,-0.06371302,0.3954228,2,-0.09305589277997829,0.3321079419566604,"[2.0501824472162616e-05, 2.7257221083085434e-21, 0.9999762897298055, 1.3326205610054285e-14, 3.208445709017214e-06]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,0G5OK5vmmg,WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts,Benchmark;Large Language Models;Classical Chinese Literature and Language Arts,6.25,2.75,Jiahuan Cao;Yang Liu;Yongxin Shi;Kai Ding;Lianwen Jin,South China University of Technology;South China University of Technology;South China University of Technology;INTSIG Information;South China University of Technology,MS student;MS student;PhD student;Researcher;Professor,https://neurips.cc/virtual/2024/poster/97880,,,,/media/PosterPDFs/NeurIPS%202024/97880.png?t=1730896668.2191207
4,27,-0.2963673,0.015343715,4,-0.22395180066953493,0.001735864936139136,"[0.009453018859470315, 1.9767024231094742e-15, 8.926228492520019e-05, 2.0283362593177226e-05, 0.9904374354930093]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,0G8AXwtmy2,T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition,harmful dataset;harmful content detection;Vision Language Model,6.5,3.75,Chen Yeh;You-Ming Chang;Wei-Chen Chiu;Ning Yu,National Yang Ming Chiao Tung University;National Yang Ming Chiao Tung University;National Chiao Tung University,MS student;MS student;Associate Professor,https://neurips.cc/virtual/2024/poster/97879,,,,/media/PosterPDFs/NeurIPS%202024/97879.png?t=1730218737.4487233
4,28,0.08612508,0.3898904,2,-0.09305589277997829,0.3321079419566604,"[0.0014088918426801514, 2.0516171034609447e-15, 0.9985910581865854, 3.328652007053601e-12, 4.996740368705417e-08]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,0Gl5WxY6es,Grounding Multimodal Large Language Models in Actions,Embodied AI;Multimodal Large Language Models;Reinforcement Learning;Imitation Learning,6.0,3.6666666666666665,Andrew Szot;Bogdan Mazoure;Harsh Agrawal;R Devon Hjelm;Zsolt Kira;Alexander T Toshev,Georgia Institute of Technology;Apple;Apple;Apple;Georgia Institute of Technology;Apple,PhD student;Research Scientist;Researcher;Researcher;Assistant Professor;research scientist,https://neurips.cc/virtual/2024/poster/96941,,,https://openreview.net/forum?id=0Gl5WxY6es,
4,29,-0.20296153,0.2345368,2,-0.09305589277997829,0.3321079419566604,"[0.0005625569601779249, 1.5361538842582905e-19, 0.9660411083187691, 2.915245786161075e-10, 0.0333963344295285]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,0Gmi8TkUC7,GenAI Arena: An Open Evaluation Platform for Generative Models,Evaluation;Benchmark;Platform;Generative Model,6.0,3.5,Dongfu Jiang;Max Ku;Tianle Li;Yuansheng Ni;Shizhuo Sun;Rongqi Fan;Wenhu Chen,Allen Institute for Artificial Intelligence;University of Waterloo;University of Waterloo;University of Toronto;NVIDIA;University of Waterloo,Intern;MS student;MS student;Undergrad student;Intern;Assistant Professor,https://neurips.cc/virtual/2024/poster/97878,,,,/media/PosterPDFs/NeurIPS%202024/97878.png?t=1730329031.3167162
4,30,-0.3021013,-0.23802479,3,-0.11151072469142234,-0.26545137332798735,"[0.13145587950910823, 7.243619237988112e-09, 1.9730680125214098e-14, 0.7878267105074053, 0.08071740273984752]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,0HRRNEAQFp,A General Protocol to Probe Large Vision Models for 3D Physical Understanding,3D physical scene understanding; Representation probing protocol; Benchmark and evaluation,6.333333333333333,4.0,Guanqi Zhan;Chuanxia Zheng;Weidi Xie;Andrew Zisserman,University of Oxford;University of Oxford;Shanghai Jiaotong University,PhD student;Postdoc;Associate Professor,https://neurips.cc/virtual/2024/poster/96940,,,https://openreview.net/forum?id=0HRRNEAQFp,/media/PosterPDFs/NeurIPS%202024/96940.png?t=1731705235.0575316
4,31,0.40233114,0.06031101,1,0.4053444721989165,-0.08263556956380372,"[0.03794477584497853, 0.9614874901117105, 1.0402785806267152e-11, 0.0005677340329079516, 2.035446058470503e-20]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0JSKjdePGq,When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL,reinforcement learning;continuous-time,6.75,3.25,Lenart Treven;Bhavya Sukhija;Yarden As;Florian Dorfler;Andreas Krause,"Swiss Federal Institute of Technology;ETHZ - ETH Zurich;Department of Computer Science, ETHZ - ETH Zurich;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96939,,,https://openreview.net/forum?id=0JSKjdePGq,/media/PosterPDFs/NeurIPS%202024/96939.png?t=1730197260.75527
4,32,-0.31179968,-0.050893012,4,-0.22395180066953493,0.001735864936139136,"[0.020483440908262252, 6.010260290168916e-14, 1.050596183258303e-06, 0.0004170439536811247, 0.9790984645418133]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,0KseSacluJ,CoFie: Learning Compact Neural Surface Representations with Coordinate Fields,Neural Surface Representation;Shape Auto-Decoding;Coordinate Field.,5.0,4.0,Hanwen Jiang;Haitao Yang;Georgios Pavlakos;Qixing Huang,University of Texas at Austin;The University of Texas at Austin;University of Texas at Austin;University of Texas at Austin,PhD student;PhD student;Assistant Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96938,,,https://openreview.net/forum?id=0KseSacluJ,
4,33,0.11298243,0.035079706,0,0.03540969834964841,0.014433900922561742,"[0.9919303895278268, 0.00019754364304979324, 9.446324995090001e-08, 0.007869298328627605, 2.674037245700041e-06]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0KvYLaTBTE,Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference,Generative models;Reinforcement learning;Decision transformer,6.333333333333333,3.0,Deqian Kong;Dehong Xu;Minglu Zhao;Bo Pang;Jianwen Xie;Andrew Lizarraga;Yuhao Huang;Sirui Xie;Ying Nian Wu,"University of California, Los Angeles;Amazon;University of California, Los Angeles;University of California, Los Angeles;Xi'an Jiaotong University;University of California, Los Angeles;University of California, Los Angeles;UCLA",PhD student;Intern;PhD student;PhD student;PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96937,,,https://openreview.net/forum?id=0KvYLaTBTE,
4,34,-0.23456638,0.06657637,4,-0.22395180066953493,0.001735864936139136,"[0.01317288362413758, 6.264026496260423e-15, 0.0009046818383638743, 5.713266585130321e-06, 0.9859167212709072]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,0LXotew9Du,KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization,Quantization;KV Cache;LLM Inference;Compression;Long Context Length,6.25,3.25,Coleman Richard Charles Hooper;Sehoon Kim;Hiva Mohammadzadeh;Michael W. Mahoney;Sophia Shao;Kurt Keutzer;Amir Gholami,"University of California, Berkeley;University of California, Berkeley;University of California, Berkeley;University of California, Berkeley",PhD student;PhD student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96936,,,https://openreview.net/forum?id=0LXotew9Du,
4,35,0.11017645,-0.16371755,3,-0.11151072469142234,-0.26545137332798735,"[0.18398949733032796, 0.10641987813314076, 7.341754273525223e-17, 0.709590616639853, 7.896678207255502e-09]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,0Lb8vZT1DB,Reliable Learning of Halfspaces under Gaussian Marginals,reliable learning;agnostic learning;halfspace;proper leaning;statistical query,7.25,2.25,Ilias Diakonikolas;Lisheng Ren;Nikos Zarifis,"University of Wisconsin - Madison;University of Wisconsin - Madison;University of Wisconsin, Madison",Full Professor;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96935,,,https://openreview.net/forum?id=0Lb8vZT1DB,
4,36,0.1429859,0.059452157,0,0.03540969834964841,0.014433900922561742,"[0.9958218950712838, 0.0002867796380267293, 3.013467615050001e-07, 0.0038906852659332325, 3.386779947984459e-07]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0LfgE6kvKZ,Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning,Federated Learning; Model Merging,5.0,3.6666666666666665,Minghui Chen;Meirui Jiang;Xin Zhang;Qi Dou;Zehua Wang;Xiaoxiao Li,"University of British Columbia;Meta Facebook;The Chinese University of Hong Kong;University of British Columbia;University of British Columbia;Department of Computer Science and Engineering, The Chinese University of Hong Kong",PhD student;Research Scientist;Assistant Professor;Researcher;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96934,,,https://openreview.net/forum?id=0LfgE6kvKZ,/media/PosterPDFs/NeurIPS%202024/96934.png?t=1731518093.5294044
4,37,-0.040502112,0.02318828,0,0.03540969834964841,0.014433900922561742,"[0.9481668806847093, 1.6167348261543632e-07, 3.5759463860152807e-06, 0.005299535040080956, 0.04652984665534099]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0Lr9HQijA1,Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations,Imprecise Label Learning,5.75,3.0,Hao Chen;Ankit Shah;Jindong Wang;Ran Tao;Yidong Wang;Xiang Li;Xing Xie;Masashi Sugiyama;Rita Singh;Bhiksha Raj,"Carnegie Mellon University;Accenture;Microsoft Research;Peking University;Microsoft Research Asia;The University of Tokyo;School of Computer Science, Carnegie Mellon University;Mohamed bin Zayed University of Artificial Intelligence",PhD student;Principal Researcher;Researcher;PhD student;Senior Principal Researcher;Full Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96933,,,https://openreview.net/forum?id=0Lr9HQijA1,/media/PosterPDFs/NeurIPS%202024/96933.png?t=1731704880.9846606
4,38,-0.06471333,0.08954511,0,0.03540969834964841,0.014433900922561742,"[0.743108421110964, 1.4135550226002838e-09, 0.001228236244033652, 0.00032273226702774036, 0.2553406089644197]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0MXzbAv8xy,GFT: Graph Foundation Model with Transferable Tree Vocabulary,Graph Foundation Model;Transferability;Computation Tree;Graph Neural Network,6.0,3.75,Zehong Wang;Zheyuan Zhang;Nitesh V Chawla;Chuxu Zhang;Yanfang Ye,University of Notre Dame;University of Notre Dame;University of Notre Dame;University of Notre Dame,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96932,,,https://openreview.net/forum?id=0MXzbAv8xy,
4,39,0.06407858,0.09707585,0,0.03540969834964841,0.014433900922561742,"[0.9990849422703857, 1.105232487769403e-06, 5.934633658676819e-05, 0.0006461632464320094, 0.00020844291410775047]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0NMzBwqaAJ,Not All Tokens Are What You Need for Pretraining,pre-training;next token prediction;data optimization;data selection,7.666666666666667,4.0,Zhenghao Lin;Zhibin Gou;Yeyun Gong;Xiao Liu;yelong shen;Ruochen Xu;Chen Lin;Yujiu Yang;Jian Jiao;Nan Duan;Weizhu Chen,Xiamen University;Microsoft;Microsoft Research Asia;Microsoft Research;Xiamen University;Tsinghua University;Microsoft;Microsoft Research Asia;Microsoft GenAI,MS student;Intern;Researcher;Researcher;Full Professor;Full Professor;Principal Researcher;Principal Researcher;Vice President,https://neurips.cc/virtual/2024/poster/96931,,,https://openreview.net/forum?id=0NMzBwqaAJ,/media/PosterPDFs/NeurIPS%202024/96931.png?t=1733724962.7310221
4,40,-0.021407472,0.09407413,0,0.03540969834964841,0.014433900922561742,"[0.9608966956017599, 1.4734600107993591e-08, 0.0005895046924904376, 0.0004414971055656476, 0.03807228786558375]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0NQzQVu9tY,DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors,representation learning;offline reinforcement learning;behavioral cloning;visual distractor,7.0,3.0,Joseph Ortiz;Antoine Dedieu;Wolfgang Lehrach;J Swaroop Guntupalli;Carter Wendelken;Ahmad Humayun;Sivaramakrishnan Swaminathan;Guangyao Zhou;Miguel Lazaro-Gredilla;Kevin Patrick Murphy,Google DeepMind;Google DeepMind;Google Deepmind;Google DeepMind;Google;Google DeepMind;Google DeepMind;Google DeepMind;Google Deepmind;Google,Researcher;Researcher;Researcher;Researcher;Researcher;Researcher;Research Engineer;Research Scientist;Research Scientist;Principal Researcher,https://neurips.cc/virtual/2024/poster/97877,,,,/media/PosterPDFs/NeurIPS%202024/97877.png?t=1733266397.4133346
4,41,-0.056248758,0.025906589,0,0.03540969834964841,0.014433900922561742,"[0.894593166202373, 5.940950524929005e-08, 6.981550968851344e-06, 0.004201893397258319, 0.10119789943989455]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0SMhqvgHST,EEVEE and GATE: Finding the right benchmarks and how to run them seamlessly,multi-modal;benchmarks;machine learning;model evaluation;benchmark frameworks,6.0,4.0,Antreas Antoniou;Eleni Triantafillou;Hugo Larochelle;Sebastien Montella;Fady Rezk;Kiyoon Kim;Linus Ericsson;Pavlos Vougiouklis;Justin Engelmann;Elliot J. Crowley;Srihari Humbarwadi;Yi Liu;Guang Yang;Jeff Z. Pan;Amos Storkey,"Google;Google;Huawei Technologies Ltd.;Samsung;Deargen;University of Edinburgh, University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh, University of Edinburgh;University of Edinburgh",Researcher;Research Scientist;Researcher;Intern;Researcher;Postdoc;Researcher;Assistant Professor;Researcher;Full Professor;Full Professor,,,,,
4,42,-0.15132618,0.02146309,4,-0.22395180066953493,0.001735864936139136,"[0.15596220463464996, 8.235454966983233e-11, 1.8097810048374016e-05, 0.0005387246806299718, 0.843480972792317]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,0SRJBtTNhX,IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors,Graph Machine Learning;Graph Data Augmentation;Graph Neural Networks,5.5,4.0,Shenghe Zheng;Hongzhi Wang;Xianglong Liu,Harbin Institute of Technology;Harbin Institute of Technology;Harbin Institute of Technology,MS student;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96930,,,https://openreview.net/forum?id=0SRJBtTNhX,/media/PosterPDFs/NeurIPS%202024/96930.png?t=1732617637.3891017
4,43,-0.18518934,0.0027779788,4,-0.22395180066953493,0.001735864936139136,"[0.07759396627060892, 1.6572327292380678e-11, 5.707009331266596e-06, 0.00044230919257670686, 0.9219580175109108]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,0T8xRFrScB,Benchmarking Counterfactual Image Generation,benchmark;causal inference;counterfactual image generation,7.25,3.75,Thomas Melistas;Nikos Spyrou;Nefeli Gkouti;Pedro Sanchez;Athanasios Vlontzos;Yannis Panagakis;Giorgos Papanastasiou;Sotirios A. Tsaftaris,"University of Athens;University of Athens;University of Athens;University of Edinburgh, University of Edinburgh;Spotify;Pfizer;University of Edinburgh",PhD student;PhD student;PhD student;PhD student;Researcher;Principal Researcher;Professor in machine learning and computer vision,https://neurips.cc/virtual/2024/poster/97876,,,,/media/PosterPDFs/NeurIPS%202024/97876.png?t=1731712408.6398222
4,44,0.5118622,-0.024860546,1,0.4053444721989165,-0.08263556956380372,"[3.492361925027581e-05, 0.999950216759063, 2.572084038714067e-19, 1.4859621686929892e-05, 1.0690467667160788e-30]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0TUMAAb3of,Queueing Matching Bandits with Preference Feedback,Bandits;Queue;Preference Feedback,6.0,2.5,Jung-hun Kim;Min-hwan Oh,Seoul National University;Seoul National University,Assistant Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96929,,,https://openreview.net/forum?id=0TUMAAb3of,/media/PosterPDFs/NeurIPS%202024/96929.png?t=1733803835.532587
4,45,-0.0018669573,0.3644946,2,-0.09305589277997829,0.3321079419566604,"[0.00037672616690704024, 1.2590230952136058e-17, 0.9996191780814375, 1.6876247336604596e-12, 4.095749967777934e-06]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,0VeSCjRDBy,Adversarial Moment-Matching Distillation of Large Language Models,Knowledge distillation;Large language models;Imitation learning;Moment-matching;Adversarial training,6.25,3.0,Chen Jia,,,https://neurips.cc/virtual/2024/poster/96928,,,https://openreview.net/forum?id=0VeSCjRDBy,/media/PosterPDFs/NeurIPS%202024/96928.png?t=1731660620.7591212
4,46,-0.24925767,0.015651966,4,-0.22395180066953493,0.001735864936139136,"[0.016966044802946473, 5.224948658148238e-14, 3.2396226905545236e-05, 4.505086653704735e-05, 0.9829565081035587]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,0WCFI2Qx85,ScaleKD: Strong Vision Transformers Could Be Excellent Teachers,knowledge distillation;model compression;training acceleration;vision transformer;convolutional neural network;multi-layer perception,6.25,4.5,Jiawei Fan;Chao Li;Xiaolong Liu;Anbang Yao,Intel Labs China;Intel;Intel,Research Intern;Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96927,,,https://openreview.net/forum?id=0WCFI2Qx85,/media/PosterPDFs/NeurIPS%202024/96927.png?t=1731695837.2500114
4,47,0.2804453,-0.1894261,1,0.4053444721989165,-0.08263556956380372,"[0.0007933086783935726, 0.9871164568117173, 9.141229584592147e-23, 0.012090234509889112, 1.5794621380108177e-18]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0XKvW4ijxp,Learning-Augmented Algorithms with Explicit Predictors,online algorithms;learning-augmented algorithms;scheduling;caching,6.0,4.0,Marek Elias;Haim Kaplan;Yishay Mansour;Shay Moran,"Bocconi University;Technion, Technion;School of Computer Science, Tel Aviv University",Assistant Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96926,,,https://openreview.net/forum?id=0XKvW4ijxp,/media/PosterPDFs/NeurIPS%202024/96926.png?t=1733319671.0065775
4,48,0.37225774,-0.11562894,1,0.4053444721989165,-0.08263556956380372,"[0.0002991283166373211, 0.9987617965879538, 8.771968479765636e-21, 0.0009390750954087835, 1.3205704493359493e-22]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0XeNkkENuI,The Road Less Scheduled,Stochastic Optimization;Optimization;Convex Optimization;Learning Rates;Learning Rate Schedules,7.5,3.5,Aaron Defazio;Xingyu Alice Yang;Ahmed Khaled;Konstantin Mishchenko;Harsh Mehta;Ashok Cutkosky,Meta;Meta;Princeton University;Samsung;Google Research;Boston University,Research Scientist;Research Engineer;PhD student;Researcher;Software Engineer;Assistant Professor,https://neurips.cc/virtual/2024/poster/96925,,,https://openreview.net/forum?id=0XeNkkENuI,/media/PosterPDFs/NeurIPS%202024/96925.png?t=1730837481.9895687
4,49,0.1460578,0.21914145,0,0.03540969834964841,0.014433900922561742,"[0.9741414927586403, 2.266433702546931e-07, 0.02584960813055069, 7.81450902772102e-06, 8.579584109672353e-07]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0ZZMUjZJYF,Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study,LLMs;Learning by Teaching;Reasoning;Mathematical Reasoning;Code Synthesis;Weak-to-Strong Generalization;In-Context Learning;Prompting;Knowledge Distillation;Education-Inspired,6.5,4.0,Xuefei Ning;Zifu Wang;Shiyao Li;Zinan Lin;Peiran Yao;Tianyu Fu;Matthew B. Blaschko;Guohao Dai;Huazhong Yang;Yu Wang,Tsinghua University;KU Leuven;Tsinghua University;Microsoft;Infinigence;Shanghai Jiaotong University;Tsinghua University;Tsinghua University;KU Leuven,Research Assistant Professor;PhD student;PhD student;Senior Researcher;Researcher;Associate Professor;Full Professor;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96924,,,https://openreview.net/forum?id=0ZZMUjZJYF,/media/PosterPDFs/NeurIPS%202024/96924.png?t=1732367562.4969194
4,50,0.07159563,-0.024327766,0,0.03540969834964841,0.014433900922561742,"[0.95323432183038, 0.00034790106998247187, 1.658151746934118e-09, 0.04639663125311332, 2.114418837226266e-05]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0ZeONp33f0,Graph Neural Networks and Arithmetic Circuits,Machine Learning;Graph Neural Networks;Arithmetic Circuits;Computational Complexity,6.5,3.25,Timon Barlag;Vivian Holzapfel;Laura Strieker;Jonni Virtema;Heribert Vollmer,Universität Hannover;Leibniz Universität Hannover;Leibniz Universität Hannover;University of Sheffield;Leibniz Universität Hannover,PhD student;Undergrad student;PhD student;Lecturer;Full Professor,https://neurips.cc/virtual/2024/poster/96923,,,https://openreview.net/forum?id=0ZeONp33f0,/media/PosterPDFs/NeurIPS%202024/96923.png?t=1732106485.9402945
4,51,-0.078428976,-0.18954016,3,-0.11151072469142234,-0.26545137332798735,"[0.21294608613980465, 7.821707473982558e-05, 2.4763735056049264e-15, 0.7862221806147088, 0.000753516170744174]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,0aN7VWwp4g,Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting,Precipitation Nowcasting;Video Prediction;Fourier Analysis;Loss Function,6.0,4.0,Chiu-Wai Yan;Shi Quan Foo;Van-Hoan Trinh;Dit-Yan Yeung;Ka-Hing Wong;Wai-Kin Wong,Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology,Chair Professor;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96922,,,https://openreview.net/forum?id=0aN7VWwp4g,/media/PosterPDFs/NeurIPS%202024/96922.png?t=1731480203.951872
4,52,-0.23586994,0.37846398,2,-0.09305589277997829,0.3321079419566604,"[2.659376908738135e-07, 1.5717914817499502e-27, 0.9999917351568274, 1.2763825327851498e-16, 7.998905481599751e-06]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,0bFXbEMz8e,FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions,generative models;material generation;chemistry;flow matching;large language models,6.0,4.333333333333333,Anuroop Sriram;Benjamin Kurt Miller;Ricky T. Q. Chen;Brandon M Wood,"Meta Facebook;University of Amsterdam;FAIR at Meta;FAIR Labs, Meta AI",Principal Researcher;PhD student;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96921,,,https://openreview.net/forum?id=0bFXbEMz8e,/media/PosterPDFs/NeurIPS%202024/96921.png?t=1730973273.143089
4,53,-0.15925287,-0.015642455,4,-0.22395180066953493,0.001735864936139136,"[0.19236616655438354, 4.2054831857800185e-10, 1.196760383256573e-06, 0.0023530509345826662, 0.8052795853301021]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,0bINeW40u4,Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning,Medical Multi-modal Alignment;Eye-gaze;Radiology,6.25,3.5,Chong Ma;Hanqi Jiang;Wenting Chen;Yiwei Li;Zihao Wu;Xiaowei Yu;Zhengliang Liu;Lei Guo;Dajiang Zhu;Tuo Zhang;Dinggang Shen;Tianming Liu;Xiang Li,"Northwest Polytechnical University Xi'an;Beijing Jiaotong University;City University of Hong Kong;University of Georgia;University of Georgia;University of Texas at Arlington, University of Texas at Arlington;University of Georgia;University of Texas at Arlington;Northwestern Polytechnical University;ShanghaiTech University;University of Georgia;Massachusetts General Hospital, Harvard University",PhD student;Undergrad student;PhD student;PhD student;PhD student;PhD student;PhD student;Assistant Professor;Associate Professor;Full Professor;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96920,,,https://openreview.net/forum?id=0bINeW40u4,
4,54,0.38273144,-0.19184409,1,0.4053444721989165,-0.08263556956380372,"[1.932117603877692e-05, 0.9995053233362603, 8.3757629992692e-26, 0.00047535548770090994, 2.0720722941364866e-25]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0cSQ1Sg7db,Generalization of Hamiltonian algorithms,Generalization;stochastic algorithms;concentration inequalities;PAC-Bayes,6.5,3.0,Andreas Maurer,,,https://neurips.cc/virtual/2024/poster/96919,,,https://openreview.net/forum?id=0cSQ1Sg7db,
4,55,-0.029614072,-0.05991212,0,0.03540969834964841,0.014433900922561742,"[0.9062697947331112, 1.2181325583609876e-05, 1.365589042131524e-09, 0.08760171170525698, 0.006116310870459291]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0cgDDa4OFr,Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation,source distribution estimation;maximum entropy;Sliced-Wasserstein distance;empirical Bayes;simulation-based inference,5.8,2.8,Julius Vetter;Guy Moss;Cornelius Schröder;Richard Gao;Jakob H. Macke,Eberhard-Karls-Universität Tübingen;Eberhard-Karls-Universität Tübingen;University Tübingen;Eberhard-Karls-Universität Tübingen,PhD student;PhD student;Postdoc;Postdoc,https://neurips.cc/virtual/2024/poster/96918,,,https://openreview.net/forum?id=0cgDDa4OFr,/media/PosterPDFs/NeurIPS%202024/96918.png?t=1733318904.6928847
4,56,-0.041920777,-0.1336057,0,0.03540969834964841,0.014433900922561742,"[0.531711044867712, 9.984463694825548e-05, 7.564993424129606e-13, 0.4668615907361474, 0.0013275197584357832]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0d50Il6enG,Non-parametric classification via expand-and-sparsify representation,non-parametric regression;non-parametric classification;expand-and-sparsify representation;universal consistency;minimax-optimal convergence rate,6.0,3.0,Kaushik Sinha,Wichita State University,Associate Professor,https://neurips.cc/virtual/2024/poster/96917,,,https://openreview.net/forum?id=0d50Il6enG,/media/PosterPDFs/NeurIPS%202024/96917.png?t=1731697679.5420048
4,57,-0.05421332,-0.22073112,3,-0.11151072469142234,-0.26545137332798735,"[0.09713941066979331, 0.0003976072592954521, 1.4254558478699268e-17, 0.902423228283062, 3.975378784918859e-05]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,0dtA21q83C,DeNetDM: Debiasing by Network Depth Modulation,Trustworthy Machine Learning;Debiasing;Robustness,6.0,3.5,Silpa Vadakkeeveetil Sreelatha;Adarsh Kappiyath;Abhra Chaudhuri;Anjan Dutta,University of Surrey;University of Exeter;University of Surrey,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96916,,,https://openreview.net/forum?id=0dtA21q83C,/media/PosterPDFs/NeurIPS%202024/96916.png?t=1733689557.490417
4,58,-0.19589648,0.09422963,4,-0.22395180066953493,0.001735864936139136,"[0.02435224020130498, 2.4447459199710374e-14, 0.0037457672845952624, 4.454089123481541e-06, 0.971897538424952]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,0e5uOaJxo1,Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure,Graph Neural Network;Protein Sequence;Structure,5.0,3.3333333333333335,Bozhen Hu;Cheng Tan;Jun Xia;Yue Liu;Lirong Wu;Jiangbin Zheng;Yongjie Xu;Yufei Huang;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University, China;National University of Singapore;Westlake University;Westlake University;Westlake University;Zhejiang University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96915,,,https://openreview.net/forum?id=0e5uOaJxo1,/media/PosterPDFs/NeurIPS%202024/96915.png?t=1730385968.8958924
4,59,0.09615892,0.18102637,0,0.03540969834964841,0.014433900922561742,"[0.9907666102293452, 1.0744602159447699e-07, 0.009167408284348564, 2.8594094494656743e-05, 3.7279945790018e-05]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0feJEykDRx,Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models,spatial-temporal data mining;location-based service;check-in sequence;large language model,5.75,4.0,Letian Gong;Yan Lin;Xinyue Zhang;Yiwen Lu;Xuedi Han;Yichen Liu;Shengnan Guo;Youfang Lin;Huaiyu Wan,Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University,PhD student;PhD student;Undergrad student;Undergrad student;MS student;Associate Professor;Full Professor;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96914,,,https://openreview.net/forum?id=0feJEykDRx,/media/PosterPDFs/NeurIPS%202024/96914.png?t=1731289337.5941467
4,60,-0.013711061,-0.07216554,0,0.03540969834964841,0.014433900922561742,"[0.865454241015452, 4.329892836552199e-05, 2.4001845122477235e-10, 0.13264639032697934, 0.001856069489184752]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0jld45XGgJ,Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?,neural collapse;deep neural collapse;unconstrained features model;deep unconstrained features model;low-rank bias,6.5,3.75,Peter Súkeník;Christoph H. Lampert;Marco Mondelli,Institute of Science and Technology;Institute of Science and Technology Austria;Institute of Science and Technology Austria,PhD student;Assistant Professor;Professor,https://neurips.cc/virtual/2024/poster/96913,,,https://openreview.net/forum?id=0jld45XGgJ,
4,61,0.49365819,-0.019841706,1,0.4053444721989165,-0.08263556956380372,"[7.822630060548342e-05, 0.999895754123991, 1.483420048202449e-18, 2.601957540343075e-05, 3.768218697311686e-29]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0l9yGPTHAU,Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms,Robust Markov decision process;norm;sample complexity;strong duality,6.5,3.0,Pierre Clavier;Laixi Shi;Erwan Le Pennec;Eric Mazumdar;Adam Wierman;Matthieu Geist,"École Polytechnique;California Institute of Technology;Ecole polytechnique;Deparment of Computing + Mathematical Sciences, California Institute of Technology;California Institute of Technology;Google",PhD student;Postdoc;Full Professor;Assistant Professor;Professor;Researcher,https://neurips.cc/virtual/2024/poster/96912,,,https://openreview.net/forum?id=0l9yGPTHAU,
4,62,-0.096782275,0.2680031,2,-0.09305589277997829,0.3321079419566604,"[0.0023653395561158497, 5.990208756032125e-17, 0.9929604081979886, 5.204758795811639e-10, 0.00467425172541959]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,0lBx844upd,ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models,network pruning;unstructured pruning;large language model;ADMM;pre-conditioned conjugate gradient;optimization,5.333333333333333,3.0,Xiang Meng;Kayhan Behdin;Haoyue Wang;Rahul Mazumder,Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology,PhD student;PhD student;PhD student;Associate Professor,https://neurips.cc/virtual/2024/poster/96911,,,https://openreview.net/forum?id=0lBx844upd,/media/PosterPDFs/NeurIPS%202024/96911.png?t=1731079283.0533488
4,63,-0.07022652,-0.30347943,3,-0.11151072469142234,-0.26545137332798735,"[0.01484313560348586, 0.0008116141139270559, 1.7329560985668576e-22, 0.9843444333188447, 8.16963742321763e-07]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,0lau89u4oE,Accelerating Non-Maximum Suppression: A Graph Theory Perspective,non-maximum suppression;object detection;graph theory,5.5,3.25,King-Siong Si;Lu Sun;Weizhan Zhang;Tieliang Gong;Jiahao Wang;Jiang Liu;Hao Sun,Xi'an Jiaotong University;Xi'an Jiaotong University;North China University of Technology;China Telecom Corporation Ltd. Data&AI Technology Company,MS student;MS student;MS student;Researcher,https://neurips.cc/virtual/2024/poster/96910,,,https://openreview.net/forum?id=0lau89u4oE,/media/PosterPDFs/NeurIPS%202024/96910.png?t=1733315333.5240822
4,64,-0.08510746,-0.26066056,3,-0.11151072469142234,-0.26545137332798735,"[0.04198070949468283, 0.0002166803539583005, 1.621964886151893e-19, 0.9577805747645664, 2.203538679253409e-05]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,0m19blQT6y,BitsFusion: 1.99 bits Weight Quantization of Diffusion Model,Diffusion;Quantization;Stable Diffusion;Low bit,5.75,4.5,Yang Sui;Yanyu Li;Anil Kag;Yerlan Idelbayev;Junli Cao;Ju Hu;Dhritiman Sagar;Bo Yuan;Sergey Tulyakov;Jian Ren,Rutgers University;Northeastern University;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Rutgers University;Snap Inc.;Snap Inc.,PhD student;PhD student;Researcher;Researcher;Researcher;Researcher;Researcher;Assistant Professor;Director of Research;Research Scientist,https://neurips.cc/virtual/2024/poster/96909,,,https://openreview.net/forum?id=0m19blQT6y,/media/PosterPDFs/NeurIPS%202024/96909.png?t=1729915675.3170154
4,65,-0.00251228,0.3769304,2,-0.09305589277997829,0.3321079419566604,"[0.00022338294547919743, 3.581316477437421e-18, 0.9997744233206917, 5.451342212454328e-13, 2.1937332839479323e-06]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,0mRouJElbZ,ProgressGym: Alignment with a Millennium of Moral Progress,Progress Alignment;AI Alignment;Large Language Models,7.666666666666667,2.6666666666666665,Tianyi Qiu;Yang Zhang;Xuchuan Huang;Jasmine Xinze Li;Jiaming Ji;Yaodong Yang,"University of California, Berkeley;Peking University;Peking University;Peking University;Peking University;Peking University",Intern;Undergrad student;Undergrad student;Intern;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/97875,,,,/media/PosterPDFs/NeurIPS%202024/97875.png?t=1731742041.9348912
4,66,0.42614552,0.08994585,1,0.4053444721989165,-0.08263556956380372,"[0.04231450222853745, 0.9574303910705185, 7.411151432469292e-11, 0.0002551066268325762, 1.6702122109388019e-21]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0nSY8NiILP,Tight Bounds for Learning RUMs from Small Slates,discrete choice;random utility model;approximation theory,6.0,2.75,Flavio Chierichetti;Mirko Giacchini;Ravi Kumar;Alessandro Panconesi;Andrew Tomkins,Sapienza University of Rome;Sapienza University of Rome;Google;Sapienza University of Rome;Google,Full Professor;PhD student;Research Scientist;Full Professor;Researcher,https://neurips.cc/virtual/2024/poster/96908,,,https://openreview.net/forum?id=0nSY8NiILP,/media/PosterPDFs/NeurIPS%202024/96908.png?t=1732698791.0319488
4,67,0.25132486,-0.20319358,1,0.4053444721989165,-0.08263556956380372,"[0.0014692736786282678, 0.9702979530629846, 8.25562080310723e-23, 0.028232773258387116, 4.133196026755348e-17]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0nzKznCjFG,Private and Personalized Frequency Estimation in a Federated Setting,federated learning;personalization;privacy,5.75,3.0,Amrith Setlur;Vitaly Feldman;Kunal Talwar,Carnegie Mellon University;Apple AI Research;Apple,PhD student;Research Scientist;Research Scientist,https://neurips.cc/virtual/2024/poster/96907,,,https://openreview.net/forum?id=0nzKznCjFG,
4,68,-0.18157998,0.03947093,4,-0.22395180066953493,0.001735864936139136,"[0.056021518140647625, 2.2409049507769265e-12, 7.766289181880335e-05, 8.693061124005051e-05, 0.9438138883540527]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,0o7Rd5jngV,Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling,Transformer;expressive power;theoretical insights,6.333333333333333,3.0,Mingze Wang;Weinan E,Peking University;Peking University,PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96906,,,https://openreview.net/forum?id=0o7Rd5jngV,
4,69,-0.12251995,-0.049827244,0,0.03540969834964841,0.014433900922561742,"[0.5933977868710371, 4.692020711095259e-08, 4.8837480611131006e-08, 0.027151412876289062, 0.37945070449498614]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0o9E8AsFgW,DarkSAM: Fooling Segment Anything Model to Segment Nothing,Segment Anything Model;Adversarial Example,6.333333333333333,4.0,Ziqi Zhou;Yufei Song;Minghui Li;Shengshan Hu;Xianlong Wang;Leo Yu Zhang;Dezhong Yao;Hai Jin,Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Griffith University;Huazhong University of Science and Technology;Huazhong University of Science and Technology,PhD student;PhD student;Assistant Professor;Associate Professor;PhD student;Researcher;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96905,,,https://openreview.net/forum?id=0o9E8AsFgW,
4,70,-0.18423451,0.25213403,2,-0.09305589277997829,0.3321079419566604,"[0.0003910223889489102, 1.2257541732558163e-19, 0.9856594802988107, 1.0341275295133388e-10, 0.013949497208827391]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,0oUutV92YF,ProtGO: Function-Guided Protein Modeling for Unified Representation Learning,Teacher-student;Knowledge Distillation;Protein Function,5.666666666666667,3.6666666666666665,Bozhen Hu;Cheng Tan;Yongjie Xu;Zhangyang Gao;Jun Xia;Lirong Wu;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University;Westlake University, China;Westlake University, China;Westlake University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96904,,,https://openreview.net/forum?id=0oUutV92YF,/media/PosterPDFs/NeurIPS%202024/96904.png?t=1730386167.5899446
4,71,-0.04843812,0.4040603,2,-0.09305589277997829,0.3321079419566604,"[2.283157915546939e-05, 4.7319779722270756e-21, 0.9999755715340707, 1.0699746750063777e-14, 1.59688676320118e-06]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,0og7nmvDbe,Confidence Regulation Neurons in Language Models,LLMs;Interpretability;Mechanistic Interpretability,7.0,3.75,Alessandro Stolfo;Ben Peng Wu;Wes Gurnee;Yonatan Belinkov;Xingyi Song;Mrinmaya Sachan;Neel Nanda,"ETHZ - ETH Zurich;University of Sheffield;Massachusetts Institute of Technology;Technion, Technion;University of Sheffield;Google DeepMind;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Assistant Professor;Lecturer;Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96903,,,https://openreview.net/forum?id=0og7nmvDbe,
4,72,0.25011468,-0.18353273,1,0.4053444721989165,-0.08263556956380372,"[0.002943043344272255, 0.9629867966703772, 1.6615624735979246e-21, 0.03407015998535021, 1.7951369123299217e-16]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0qb8KoPsej,Accelerating Matroid Optimization through Fast Imprecise Oracles,matroid optimization;weak-strong models;learning-augmented algorithms;algorithms with predictions;query minimization;robustness,5.5,2.75,Franziska Eberle;Felix Hommelsheim;Alexander Lindermayr;Zhenwei Liu;Nicole Megow;Jens Schlöter,Technische Universität Berlin;Universität Bremen;Universität Bremen;Universität Bremen;Universität Bremen,Postdoc;Postdoc;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96902,,,https://openreview.net/forum?id=0qb8KoPsej,
4,73,0.24778247,-0.18444899,1,0.4053444721989165,-0.08263556956380372,"[0.003110199854209833, 0.9603684482570413, 1.6970410536606683e-21, 0.036521351888748645, 2.345698729605272e-16]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0rl5vWOzRU,Score-Optimal Diffusion Schedules,Diffusion model;adaptive schedule;Annealed Langevin,6.0,3.0,Christopher Williams;Andrew Campbell;Arnaud Doucet;Saifuddin Syed,University of Oxford;University of Oxford;University of Oxford;University of Oxford,PhD student;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96901,,,https://openreview.net/forum?id=0rl5vWOzRU,
4,74,-0.17648138,-0.41862112,3,-0.11151072469142234,-0.26545137332798735,"[0.0018563943535816088, 8.874589275115064e-05, 2.4688467506745845e-28, 0.9980547737775745, 8.597609256401038e-08]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,0sJBW05a2W,3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration,Point Cloud Registration;Focus and Matching,5.666666666666667,4.333333333333333,Liyuan Zhang;Le Hui;qi liu;Bo Li;Yuchao Dai,Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwestern Polytechnical University Xi'an;Northwestern Polytechnical University,MS student;Associate Professor;Researcher;Associate Professor;Professor,https://neurips.cc/virtual/2024/poster/96900,,,https://openreview.net/forum?id=0sJBW05a2W,/media/PosterPDFs/NeurIPS%202024/96900.png?t=1731333373.8074756
4,75,-0.16704087,-0.3598848,3,-0.11151072469142234,-0.26545137332798735,"[0.005856073867272209, 4.209472433668435e-05, 1.5954675816149296e-24, 0.9940994989385624, 2.3324698287643913e-06]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,0sycTGl4In,4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization,Dynamic Novel View Synthesis;4D Gaussian splatting;Sparse reconstruction;in-the-wild,5.333333333333333,4.666666666666667,Mijeong Kim;Jongwoo Lim;Bohyung Han,Seoul National University;Seoul National University,Full Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96899,,,https://openreview.net/forum?id=0sycTGl4In,/media/PosterPDFs/NeurIPS%202024/96899.png?t=1733712090.5881364
4,76,0.61073065,0.018717432,1,0.4053444721989165,-0.08263556956380372,"[4.280494815207649e-06, 0.9999949454008019, 1.7349707719856584e-19, 7.741043828175231e-07, 8.115441125877869e-38]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,0uGlKYS7a2,Maximizing utility in multi-agent environments by anticipating the behavior of other learners,Game Theory; no regret; learning theory;,5.5,3.25,Angelos Assos;Yuval Dagan;Constantinos Costis Daskalakis,Massachusetts Institute of Technology;Massachusetts Institute of Technology,MS student;Full Professor,https://neurips.cc/virtual/2024/poster/96898,,,https://openreview.net/forum?id=0uGlKYS7a2,/media/PosterPDFs/NeurIPS%202024/96898.png?t=1731753379.9098587
4,77,-0.07488669,0.3827278,2,-0.09305589277997829,0.3321079419566604,"[2.418467784422178e-05, 3.3685030310730993e-21, 0.9999685997880517, 2.73473382164788e-14, 7.215534076797433e-06]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,0uXtFk5KNJ,BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models,block coordinate descent;large language models,5.25,3.75,Qijun Luo;Hengxu Yu;Xiao Li,"The Chinese University of Hong Kong, Shenzhen;The Chinese University of Hong Kong, Shenzhen;Chinese University of Hong Kong Shen Zhen",PhD student;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96897,,,https://openreview.net/forum?id=0uXtFk5KNJ,/media/PosterPDFs/NeurIPS%202024/96897.png?t=1733743857.9232197
4,78,0.022653038,0.24370801,2,-0.09305589277997829,0.3321079419566604,"[0.2225021168521947, 2.020816290104222e-11, 0.776272096409546, 2.968088976839367e-07, 0.0012254899091534302]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,0zFVhMBZHJ,Mixture of Tokens: Continuous MoE through Cross-Example Aggregation,LLM;Mixture of Experts;MoE;conditional computation;fully-differentiable;language modeling,6.0,3.6666666666666665,Szymon Antoniak;Michał Krutul;Maciej Pióro;Jakub Krajewski;Jan Ludziejewski;Kamil Ciebiera;Krystian Król;Tomasz Odrzygóźdź;Marek Cygan;Sebastian Jaszczur,IDEAS NCBR Sp.;IDEAS NCBR Sp.;University of Warsaw;University of Warsaw;IDEAS NCBR Sp.;University of Warsaw;IDEAS NCBR;Nomagic;University of Warsaw,PhD student;Researcher;PhD student;PhD student;Intern;MS student;Postdoc;Founder / CTO;PhD student,https://neurips.cc/virtual/2024/poster/96896,,,https://openreview.net/forum?id=0zFVhMBZHJ,/media/PosterPDFs/NeurIPS%202024/96896.png?t=1730308223.324062
4,79,0.24368975,0.18879418,0,0.03540969834964841,0.014433900922561742,"[0.9995454868214059, 0.0001237858437699931, 0.00028076553269042355, 4.996167994756796e-05, 1.2218614751301206e-10]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,0zWzJj6lO3,Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents,cooperative AI;AI safety;LLM agents;cognitive science;language model evaluation;dynamic evaluation;alignment;agency;evolving benchmarks;multi-agent interactions,5.75,3.5,Giorgio Piatti;Zhijing Jin;Max Kleiman-Weiner;Bernhard Schölkopf;Mrinmaya Sachan;Rada Mihalcea,Common Sense Machines;University of Michigan;Swiss Federal Institute of Technology,Principal Researcher;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96895,,,https://openreview.net/forum?id=0zWzJj6lO3,
4,80,-0.16938657,-0.05973538,4,-0.22395180066953493,0.001735864936139136,"[0.2624558376947698, 2.896694867681216e-09, 4.1515783380971504e-08, 0.013473520676718457, 0.7240705972160334]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,0zfUiSX5si,AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases,De Novo Peptide sequencing;Proteomics;Mass Spectrum,5.333333333333333,3.0,Jun Xia;Shaorong Chen;Jingbo Zhou;Xiaojun Shan;Wenjie Du;Zhangyang Gao;Cheng Tan;Bozhen Hu;Jiangbin Zheng;Stan Z. Li,"Westlake University, China;Westlake University;Jilin University;University of Electronic Science and Technology of China;University of Science and Technology of China;Westlake University, China;Zhejiang University & Westlake University;Westlake University;Westlake University;Westlake University",PhD student;PhD student;Undergrad student;Undergrad student;Assistant Professor;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96894,,,https://openreview.net/forum?id=0zfUiSX5si,
4,81,-0.25151917,-0.28693447,3,-0.11151072469142234,-0.26545137332798735,"[0.038782136261740624, 2.5102115126744253e-07, 2.6422960906726622e-18, 0.9588877078968406, 0.002329904820267498]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,105ZuvpdyW,SegVol: Universal and Interactive Volumetric Medical Image Segmentation,Volumetric Medical Image Segmentation;3D Segmentation Foundation Model;Universal and Interactive 3D Segmentation,7.666666666666667,4.333333333333333,Yuxin Du;Fan BAI;Tiejun Huang;Bo Zhao,Beijing Academy of Artificial Intelligence;The Chinese University of Hong Kong;Peking University;BAAI,Intern;PhD student;Full Professor;Principal Researcher,https://neurips.cc/virtual/2024/poster/96893,,,https://openreview.net/forum?id=105ZuvpdyW,/media/PosterPDFs/NeurIPS%202024/96893.png?t=1731410503.871179
4,82,0.04577409,-0.24324691,3,-0.11151072469142234,-0.26545137332798735,"[0.03918922357500033, 0.030258312222937064, 1.372321890435455e-20, 0.9305524473636942, 1.683836828893913e-08]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,1067784F6e,Data Distribution Valuation,Data distribution valuation;Huber model;Maximum mean discrepancy,6.333333333333333,4.333333333333333,Xinyi Xu;Shuaiqi Wang;Chuan-Sheng Foo;Bryan Kian Hsiang Low;Giulia Fanti,"National University of Singapore;Carnegie Mellon University;Institute for Infocomm Research, A*STAR;National University of Singapore;Carnegie Mellon University",PhD student;PhD student;Principal Scientist;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96892,,,https://openreview.net/forum?id=1067784F6e,/media/PosterPDFs/NeurIPS%202024/96892.png?t=1731176029.7581189
4,83,-0.22563006,-0.049784996,4,-0.22395180066953493,0.001735864936139136,"[0.06476875497351639, 2.154537655378956e-11, 1.7787347822670647e-07, 0.0018620508812073528, 0.9333690162502525]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,12A1RT1L87,Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?,Dataset Condensation;Dataset Distillation,5.666666666666667,3.6666666666666665,Lingao Xiao;Yang He,"School of Computer Science and  Engineering, Nanyang Technological University;Institute of High Performance Computing, Singapore, A*STAR",Undergrad student;Researcher,https://neurips.cc/virtual/2024/poster/96891,,,https://openreview.net/forum?id=12A1RT1L87,/media/PosterPDFs/NeurIPS%202024/96891.png?t=1731138766.8349779
4,84,-0.20074943,0.040258985,4,-0.22395180066953493,0.001735864936139136,"[0.034360896276111, 4.51758880193246e-13, 9.594177959258861e-05, 4.712981119010438e-05, 0.9654960321326544]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,135eKqDoRR,Bayesian-guided Label Mapping for Visual Reprogramming,visual reprogramming;adversarial reprogramming;output label mapping;Bayesian probability,7.25,4.0,Chengyi Cai;Zesheng Ye;Lei Feng;Jianzhong Qi;Feng Liu,University of Melbourne;Singapore University of Technology and Design;University of Melbourne;University of Melbourne,PhD student;Assistant Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96890,,,https://openreview.net/forum?id=135eKqDoRR,
4,85,-0.1496939,0.30529067,2,-0.09305589277997829,0.3321079419566604,"[7.671898148386883e-05, 9.364668132294178e-21, 0.9991654936727183, 2.2003330780314105e-12, 0.000757787343597433]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,14hLJr6kZ3,Enhancing Domain Adaptation through Prompt Gradient Alignment,transfer learning; domain adaptation; prompt-tuning,6.25,3.25,Hoang Phan;Tung Lam Tran;Quyen Tran;Trung Le,VinAi Research;VinAI Research;Monash University;New York University,Research resident;Research Resident;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96889,,,https://openreview.net/forum?id=14hLJr6kZ3,/media/PosterPDFs/NeurIPS%202024/96889.png?t=1732036918.0147438
4,86,0.2630342,0.051892787,0,0.03540969834964841,0.014433900922561742,"[0.9043817304141594, 0.08696693101124121, 4.94767890802531e-09, 0.008651333623030824, 3.889727227343328e-12]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,15460JjocO,Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners,multi-agent;reinforcement learning;robustness;diversity;specialization,7.0,3.6666666666666665,Rujikorn Charakorn;Poramate Manoonpong;Nat Dilokthanakul,Sakana AI;Vidyasirimedhi Institute of Science and Technology;King Mongkut's Institute of Technology Ladkrabang,Intern;Full Professor;Lecturer,https://neurips.cc/virtual/2024/poster/96888,,,https://openreview.net/forum?id=15460JjocO,/media/PosterPDFs/NeurIPS%202024/96888.png?t=1731395258.7214391
4,87,0.61719507,-0.024593957,1,0.4053444721989165,-0.08263556956380372,"[9.868338786504212e-07, 0.9999983047922121, 5.564337010276933e-22, 7.083739092715962e-07, 2.357120238122563e-39]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,15Jm9v7wCo,No-Regret Learning for Fair Multi-Agent Social Welfare Optimization,Online Learning;Nash Social Welfare,5.666666666666667,3.3333333333333335,Mengxiao Zhang;Ramiro Deo-Campo Vuong;Haipeng Luo,University of Southern California;University of Southern California,Undergrad student;Associate Professor,https://neurips.cc/virtual/2024/poster/96887,,,https://openreview.net/forum?id=15Jm9v7wCo,
4,88,-0.14552048,-0.15470643,3,-0.11151072469142234,-0.26545137332798735,"[0.4506017573119636, 1.4318651032904615e-06, 2.355930290528217e-12, 0.47977492314473086, 0.06962188767584615]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,15PS30UOUp,Kuro Siwo: 33 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping,Synthetic Aperture Radar;SAR;Deep Learning;Remote Sensing;Floods;dataset,6.75,3.75,Nikolaos Ioannis Bountos;Maria Sdraka;Angelos Zavras;Andreas Karavias;Ilektra Karasante;Themistocles Herekakis;Angeliki Thanasou;Dimitrios Michail;Ioannis Papoutsis,National Observatory of Athens;National Observatory of Athens;Harokopio University;The Centre for Research & Technology;National Observatory of Athens ;National Observatoty of Athens;National Observatory of Athens;Harokopio University;National Technical University of Athens,PhD student;Researcher;PhD student;Researcher;Researcher;Researcher;Researcher;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97874,,,,
4,89,0.004352061,-0.07103703,0,0.03540969834964841,0.014433900922561742,"[0.8611335122967432, 9.745017840476688e-05, 1.4911695346313873e-10, 0.13812047879067313, 0.0006485585850620186]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,164QnJsYjF,Dense Associative Memory Through the Lens of Random Features,Associative Memory;Kernels;Random Features;Hopfield Network,6.0,3.0,Benjamin Hoover;Duen Horng Chau;Hendrik Strobelt;Parikshit Ram;Dmitry Krotov,International Business Machines;International Business Machines;International Business Machines;Massachusetts Institute of Technology;Georgia Institute of Technology,AI Research Engineer;Principal Researcher;Principal Researcher;Researcher;Full Professor,https://neurips.cc/virtual/2024/poster/96886,,,https://openreview.net/forum?id=164QnJsYjF,/media/PosterPDFs/NeurIPS%202024/96886.png?t=1733846086.053208
4,90,-0.31772932,0.41427824,2,-0.09305589277997829,0.3321079419566604,"[6.495458653404156e-09, 1.501825701305835e-32, 0.999999791185862, 2.928553667208369e-19, 2.0231867928563216e-07]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,168NLzTpw8,Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation,Vision-Language;Region-Level Understanding;Multimodal Large Language Model,5.75,3.75,Yaoyuan Liang;Zhuojun Cai;Jian Xu;Guanbo Huang;Yiran Wang;Xiao Liang;Jiahao Liu;Ziran Li;Jingang Wang;Shao-Lun Huang,"Tsinghua Shenzhen International Graduate School, Tsinghua University;Microsoft;University of Electronic Science and Technology of China;Tsinghua University;Tsinghua University;Meituan;Meituan;Tsinghua University",PhD student;Intern;Undergrad student;MS student;MS student;Researcher;Researcher;Associate Professor,https://neurips.cc/virtual/2024/poster/96885,,,https://openreview.net/forum?id=168NLzTpw8,
4,91,-0.118134014,0.26676714,2,-0.09305589277997829,0.3321079419566604,"[0.0013393624132133227, 1.0137078633830586e-17, 0.9926958756296962, 2.7351284977193136e-10, 0.005964761683577465]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,181llen2gw,A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks,Vision-Language Model;Fairness;Debias,6.333333333333333,3.6666666666666665,Hoin Jung;Taeuk Jang;Xiaoqian Wang,Purdue University;Purdue University;Purdue University,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96884,,,https://openreview.net/forum?id=181llen2gw,/media/PosterPDFs/NeurIPS%202024/96884.png?t=1731379505.2628894
4,92,-0.19037005,0.30377576,2,-0.09305589277997829,0.3321079419566604,"[2.429404286825691e-05, 2.5523456476012193e-22, 0.9992557499000684, 5.799779560071188e-13, 0.0007199560564833011]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,18FGRNd0wZ,Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation,tokenization of crystals;language models;materials generation,6.0,3.5,Keqiang Yan;Xiner Li;Hongyi Ling;Kenna Ashen;Carl Edwards;Raymundo Arroyave;Marinka Zitnik;Heng Ji;Xiaofeng Qian;Xiaoning Qian;Shuiwang Ji,"Texas A&M University;Texas A&M University - College Station;Texas A&M University - College Station;Texas A&M University - College Station;Genentech;Texas A&M University Main Campus;Harvard University;University of Illinois, Urbana-Champaign;Texas A&M University;Texas A&M;Texas A&M University",PhD student;PhD student;PhD student;PhD student;Intern;Assistant Professor;Full Professor;Associate Professor;Full Professor;Professor,https://neurips.cc/virtual/2024/poster/96883,,,https://openreview.net/forum?id=18FGRNd0wZ,/media/PosterPDFs/NeurIPS%202024/96883.png?t=1733428872.6393995
4,93,-0.18803668,0.09546091,4,-0.22395180066953493,0.001735864936139136,"[0.029344324465792094, 4.331804966730316e-14, 0.003825404257415033, 5.330131133702502e-06, 0.9668249411456159]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,18RdkSv9h9,FINALLY: fast and universal speech enhancement with studio-like quality,speech enhancement; generative models,6.5,4.75,Nicholas Babaev;Kirill Tamogashev;Azat Saginbaev;Ivan Shchekotov;Hanbin Bae;Hosang Sung;WonJun Lee;Hoon-Young Cho;Pavel Andreev,"Samsung;Skolkovo Institute of Science and Technology;Moscow Institute of Physics and Technology;Samsung;Samsung;Samsung;Higher School of Economics, Higher School of Economics",Researcher;MS student;MS student;Principal Researcher;Researcher;Vice President;MS student,https://neurips.cc/virtual/2024/poster/96882,,,https://openreview.net/forum?id=18RdkSv9h9,/media/PosterPDFs/NeurIPS%202024/96882.png?t=1731683595.700073
4,94,0.32727078,-0.11709024,1,0.4053444721989165,-0.08263556956380372,"[0.0015143784292728018, 0.9944340591905692, 1.3563297738908797e-19, 0.00405156238015796, 1.4188072370885738e-19]","[0.015873939496395848, 0.01212153865264238]",0.18458468089349292,1ATLLgvURu,Learning-Augmented Priority Queues,learning-augmented algorithms;algorithms with predictions;priority queue;shortest paths;Dijkstra,5.75,4.25,Ziyad Benomar;Christian Coester,University of Oxford,Associate Professor,https://neurips.cc/virtual/2024/poster/96881,,,https://openreview.net/forum?id=1ATLLgvURu,
4,95,0.3095995,0.5030761,2,-0.09305589277997829,0.3321079419566604,"[0.006953947932559051, 7.836472844357434e-12, 0.9930460520593337, 2.7082453266095287e-13, 1.5816830500637508e-16]","[0.018758953909708158, 0.005503138660508686]",0.1901804688113724,1BZKqZphsW,Risk-Averse Fine-tuning of Large Language Models,Risk Averse Reinforcement Learning;Large Language Model Finetuning,5.8,3.2,Sapana Chaudhary;Ujwal Dinesha;Dileep Kalathil;Srinivas Shakkottai,Texas A&M University;Texas A&M University - College Station;Texas A&M University;Texas A&M,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96880,,,https://openreview.net/forum?id=1BZKqZphsW,/media/PosterPDFs/NeurIPS%202024/96880.png?t=1733328781.5713553
4,96,-0.26364937,-0.38828564,3,-0.11151072469142234,-0.26545137332798735,"[0.0042742346784622205, 1.2213664358141939e-06, 1.0392331157227113e-24, 0.9957172288281398, 7.315126962220181e-06]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,1CssOqRYyz,Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds,compression;point cloud;diffusion,4.0,4.0,Kai Liu;Kang You;Pan Gao,"Nanjing University of Aeronautics and Astronautics;Nanjing university;Nanjing University of Aeronautics and Astronautics, Tsinghua University",MS student;PhD student;Associate Professor,,,,,
4,97,-0.25224024,-0.31188005,3,-0.11151072469142234,-0.26545137332798735,"[0.02181397045031035, 4.083523029119754e-07, 7.011404530938188e-20, 0.9776265178239067, 0.0005591033734800647]","[0.01685061411332374, 0.009038605707132968]",0.19454597371203433,1Du3mMP5YN,Learning to Shape In-distribution Feature Space for Out-of-distribution Detection,Out-of-distribution Detection,5.75,4.0,Yonggang Zhang;Jie Lu;Bo Peng;Zhen Fang;Yiu-ming Cheung,Hong Kong Baptist University;University of Technology Sydney;University of Technology Sydney,Postdoc;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96879,,,https://openreview.net/forum?id=1Du3mMP5YN,/media/PosterPDFs/NeurIPS%202024/96879.png?t=1731745181.7993424
4,98,-0.30068702,-0.14781809,4,-0.22395180066953493,0.001735864936139136,"[0.12467688706770812, 9.50142444776455e-11, 3.416578368787478e-10, 0.05858550016165793, 0.8167376123339619]","[0.004356315034084873, 0.0058261532468214805]",0.19540128792965328,1ELFGSNBGC,Multiview Scene Graph,scene representation; spatial understanding; place recognition; object correspondence; scene graph,5.25,3.25,Juexiao Zhang;Gao Zhu;Sihang Li;Xinhao Liu;Haorui Song;Xinran Tang;Chen Feng,New York University;New York University;New York University;New York University;New York University;New York University;New York University,PhD student;MS student;PhD student;PhD student;MS student;MS student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96878,,,https://openreview.net/forum?id=1ELFGSNBGC,/media/PosterPDFs/NeurIPS%202024/96878.png?t=1731728482.5838113
4,99,-0.09486352,0.005280091,0,0.03540969834964841,0.014433900922561742,"[0.6609734801875284, 1.576882577967449e-08, 3.067806686657954e-06, 0.005314752454231667, 0.33370868378272756]","[0.01756078903975236, 0.012594834546802082]",0.23528758865344707,1F32iCJFfa,Schrodinger Bridge Flow for Unpaired Data Translation,unpaired data translation;diffusion models;Schrodinger bridge;bridge matching;stochastic interpolant;flow matching,6.5,4.0,Valentin De Bortoli;Iryna Korshunova;Andriy Mnih;Arnaud Doucet,University of Oxford;Google DeepMind;Google DeepMind;University of Oxford,Postdoc;Researcher;Research Scientist;Full Professor,https://neurips.cc/virtual/2024/poster/96877,,,https://openreview.net/forum?id=1F32iCJFfa,/media/PosterPDFs/NeurIPS%202024/96877.png?t=1731688420.732189
5,0,0.08799766,-0.06060414,0,0.046218503789983885,0.004953785986959865,"[0.9489496670368213, 0.00556954628943185, 2.5454026071545938e-11, 0.045341673265947985, 0.00013911338234487013]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,00Sx577BT3,The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning,numerical simulations;fluid-dynamics;partial differential equations;operator learning,6.666666666666667,3.6666666666666665,Ruben Ohana;Michael McCabe;Lucas Thibaut Meyer;Rudy Morel;Fruzsina Julia Agocs;Miguel Beneitez;Marsha Berger;Blakesley Burkhart;Stuart B. Dalziel;Drummond Buschman Fielding;Daniel Fortunato;Jared A. Goldberg;Keiya Hirashima;Yan-Fei Jiang;Rich Kerswell;Suryanarayana Maddu;Jonah M. Miller;Payel Mukhopadhyay;Stefan S. Nixon;Jeff Shen;Romain Watteaux;Bruno Régaldo-Saint Blancard;François Rozet;Liam Holden Parker;Miles Cranmer;Shirley Ho,"Flatiron Institute;University of Colorado, Boulder;INRIA;Flatiron Institute;Flatiron Institute;University of Cambridge;Flatiron Institute;Rutgers University;University of Cambridge;Simons Foundation;Flatiron Institute;Flatiron Institute;Simons Foundation;University of Cambridge;Flatiron Institute/Simons Foundation;Los Alamos National Laboratory;University of California, Berkeley;University of Cambridge;Princeton University;CEA;Flatiron Institute;Flatiron Institute;Flatiron Institute;University of Cambridge;Carnegie Mellon University;The University of Tokyo",Postdoc;PhD student;PhD student;Postdoc;Postdoc;Postdoc;Full Professor;Assistant Professor;Director of the GK Batchelor Laboratory;Postdoc;Researcher;Postdoc;Researcher;Full Professor;Postdoc;Researcher;Postdoc;PhD student;PhD student;Researcher;Postdoc;Intern;Researcher;Assistant Professor;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/97882,,,,
5,1,-0.08406016,0.2851326,2,-0.09354076594739029,0.33204128402332034,"[0.0009077692248581963, 7.273800994735487e-16, 0.9965058074074137, 9.738734147963813e-14, 0.0025864233676299517]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,00uVk06eVK,On the Noise Robustness of In-Context Learning for Text Generation,In-Context Learning;Large Language Models;Noise Robustness,6.333333333333333,3.0,Hongfu Gao;Feipeng Zhang;Wenyu Jiang;Jun Shu;Feng Zheng;Hongxin Wei,Xi'an Jiaotong University;Xi'an Jiaotong University;Nanjing University;Xi'an Jiaotong University;Southern University of Science and Technology;Southern University of Science and Technology,MS student;Full Professor;PhD student;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96962,,,https://openreview.net/forum?id=00uVk06eVK,/media/PosterPDFs/NeurIPS%202024/96962.png?t=1731587881.4159098
5,2,-0.16364236,-0.11411294,4,-0.21275706367934288,-0.0031904620518618575,"[0.3225513503280762, 4.3702490818671184e-07, 2.632910245128399e-10, 0.04945807246108383, 0.6279901399226406]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,01I55gys19,Few-Class Arena: A Benchmark for Efficient Vision Model Selection and Dataset Difficulty,few-class;efficiency;neural network;convolutional neural network;transformer;dataset difficulty measurement;scaling law,5.0,3.3333333333333335,Bryan Bo Cao;Lawrence O'Gorman;Michael Coss;Shubham Jain,Nokia networks GmbH;State University of New York at Stony Brook,Intern;Assistant Professor,,,,,
5,3,0.07371062,-0.27021888,3,-0.12286635144929052,-0.2829108388789275,"[0.046264125465655115, 0.13811003352370546, 7.435291613781795e-23, 0.8156257090580263, 1.3195261307562812e-07]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,01XV5Za56k,Testing Calibration in Nearly-Linear Time,Calibration;Property testing;Linear programming,6.25,3.25,Lunjia Hu;Arun Jambulapati;Kevin Tian;Chutong Yang,Stanford University;Stanford University;Stanford University;University of Texas at Austin,PhD student;PhD student;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96961,,,https://openreview.net/forum?id=01XV5Za56k,
5,4,-0.1284643,0.3103237,2,-0.09354076594739029,0.33204128402332034,"[5.8157647114181893e-05, 1.5821411437287645e-18, 0.9991064009174165, 7.961530835266717e-16, 0.0008354414354682552]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,01lhHg8H9p,GLBench: A Comprehensive Benchmark for Graph with Large Language Models,Graph learning;Large Language Model;Zero-Shot,6.75,4.0,Yuhan Li;Peisong Wang;Xiao Zhu;Aochuan Chen;Haiyun Jiang;Deng Cai;Victor Wai Kin Chan;Jia Li,"Hong Kong University of Science and Technology;Tsinghua University;Beijing University of Posts and Telecommunications;Hong Kong University of Science and Technology;Tencent AI Lab;Tencent AI Lab;Shenzhen International Graduate School, Tsinghua University;Hong Kong University of Science and Technology",PhD student;MS student;Undergrad student;PhD student;Researcher;Research Scientist;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97881,,,,/media/PosterPDFs/NeurIPS%202024/97881.png?t=1731478194.2539835
5,5,-0.23808402,0.26056772,2,-0.09354076594739029,0.33204128402332034,"[1.0244051670656859e-05, 2.397215313163422e-20, 0.9933655965093229, 3.4981976986853025e-15, 0.006624159439002853]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,01qa1ZJs65,Bridge the Modality and Capability Gaps in Vision-Language Model Selection,Vision-Language Model;Model Selection;Zero-Shot Image Classification,5.25,4.0,Chao Yi;Yuhang He;De-Chuan Zhan;Han-Jia Ye,Nanjing University;Nanjing University;Nanjing University;Nanjing University,MS student;Undergrad student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96960,,,https://openreview.net/forum?id=01qa1ZJs65,/media/PosterPDFs/NeurIPS%202024/96960.png?t=1731123927.9174762
5,6,-0.10493148,-0.30384988,3,-0.12286635144929052,-0.2829108388789275,"[0.0423418668702068, 0.00036569113861611, 5.001776601713997e-22, 0.9572255991014478, 6.684288972912105e-05]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,01s5ODIHKd,FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space,deep watermarking;latent frequency optimization,5.5,3.75,YiYang Guo;Ruizhe Li;Mude Hui;Hanzhong Allan Guo;Chen Zhang;Chuangjian Cai;Le Wan;Shangfei Wang,"University of Science and Technology of China;University of California, Santa Cruz;Renmin University of China;Tsinghua University;University of Science and Technology of China;University of Science and Technology of China",MS student;PhD student;MS student;PhD student;Full Professor;PhD student,https://neurips.cc/virtual/2024/poster/96959,,,https://openreview.net/forum?id=01s5ODIHKd,/media/PosterPDFs/NeurIPS%202024/96959.png?t=1730176108.8718698
5,7,-0.295713,-0.42771262,3,-0.12286635144929052,-0.2829108388789275,"[0.00683393948718768, 2.0318838808962336e-06, 6.195601751736563e-27, 0.9931570274306016, 7.001198329584394e-06]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,02CIZ8qeDc,PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection,3D anomaly detection;Zero-shot 3D anomaly detection,6.0,3.6666666666666665,Qihang Zhou;Jiangtao Yan;Shibo He;Wenchao Meng;Jiming Chen,Zhejiang University;Zhejiang University;Zhejiang University;Zhejiang University,PhD student;MS student;Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96958,,,https://openreview.net/forum?id=02CIZ8qeDc,/media/PosterPDFs/NeurIPS%202024/96958.png?t=1731476864.9817398
5,8,-0.3188932,-0.023905918,4,-0.21275706367934288,-0.0031904620518618575,"[0.002432524578302704, 1.4476867892299477e-13, 9.505556685046896e-06, 1.0563891623333758e-05, 0.9975474059732441]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,02HWT9c4Lp,Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion,Semantic Scene completion，Voxel Proposal，Knowledge Distillation,5.5,4.0,Lubo Wang;Di Lin;Kairui Yang;Ruonan Liu;Qing Guo;Wuyuan Xie;Miaohui Wang;Lingyu Liang;Yi Wang;Ping Li,"Tianjin University;Tianjin University;Tianjin University;Tianjin University; Agency for Science, Technology and Research (A*STAR));Department of Software Engineering, Shenzhen University;Shenzhen University;South China University of Technology;Shenzhen University;The Hong Kong Polytechnic University",MS student;Associate Professor;PhD student;Associate Professor;Researcher;Associate Professor;Associate Professor;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96957,,,https://openreview.net/forum?id=02HWT9c4Lp,/media/PosterPDFs/NeurIPS%202024/96957.png?t=1731159292.6143699
5,9,0.52375084,0.03593809,1,0.4007888716927687,-0.08240049330680303,"[3.5110478332878854e-05, 0.999962572786286, 2.2468724180679707e-16, 2.3167353808909836e-06, 9.603052638692236e-23]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,02r24A8doi,Achieving Constant Regret in Linear Markov Decision Processes,Reinforcement learning;Constant regret;Misspecified linear MDP,5.25,2.75,Weitong Zhang;Zhiyuan Fan;Jiafan He;Quanquan Gu,"Massachusetts Institute of Technology;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles",PhD student;PhD student;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96956,,,https://openreview.net/forum?id=02r24A8doi,
5,10,-0.24769914,0.06194072,4,-0.21275706367934288,-0.0031904620518618575,"[0.002934846755503228, 7.696226644935728e-14, 0.0008874823625213888, 1.9399803222274555e-07, 0.9961774768838662]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,04EC4ZnZJj,MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers,transformer architecture;large language model;computational complexity reduction,6.0,3.5,Ning Ding;Yehui Tang;Haochen Qin;Zhenli Zhou;Chao Xu;Lin Li;Kai Han;Liao Heng;Yunhe Wang,"Peking University;Huawei Technologies Ltd.;Huawei Technologies Ltd.;Peking University;Peking University;Huawei Noah's Ark Lab;, Tsinghua University;Huawei Noah's Ark Lab",PhD student;Researcher;Researcher;MS student;Full Professor;Principal Researcher;Principal Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96955,,,https://openreview.net/forum?id=04EC4ZnZJj,
5,11,0.45866024,0.07679337,1,0.4007888716927687,-0.08240049330680303,"[0.0025869204898794, 0.997402284099022, 1.7175689073687871e-12, 1.0795409381156098e-05, 3.2796751001412715e-18]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,06JRFVK88O,Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games,Multi-agent Reinforcement Learning;Imitation Learning,6.666666666666667,3.0,The Viet Bui;Tien Anh Mai;Thanh Hong Nguyen,Singapore Management University;University of Oregon;Singapore Management University,Assistant Professor;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96954,,,https://openreview.net/forum?id=06JRFVK88O,/media/PosterPDFs/NeurIPS%202024/96954.png?t=1731744891.8886228
5,12,-0.21952832,-0.2596673,3,-0.12286635144929052,-0.2829108388789275,"[0.08866306161827243, 2.405302127684747e-06, 3.334073386029925e-17, 0.8969018294698425, 0.014432703609757298]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,06Vt6f2js7,SyncTweedies: A General Generative Framework Based on Synchronized Diffusions,Diffusion Models;Synchronization;Texturing;3D Gaussian Splatting;Mesh;Panorama,6.666666666666667,3.6666666666666665,Jaihoon Kim;Juil Koo;Kyeongmin Yeo;Minhyuk Sung,KAIST;Adobe Systems;Korea Advanced Institute of Science & Technology;Korea Advanced Institute of Science & Technology,MS student;Intern;Undergrad student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96953,,,https://openreview.net/forum?id=06Vt6f2js7,
5,13,0.5387558,-0.021885695,1,0.4007888716927687,-0.08240049330680303,"[2.8408802071161274e-06, 0.9999946877817689, 6.709516347521414e-20, 2.4713380240407607e-06, 1.3554946078658176e-24]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,07N0qoaZ2L,Improved Analysis for Bandit Learning in Matching Markets,Bandits;Matching markets;Stable matching;Stable regret;Exploration and exploitation;$\alpha$-condition,5.5,3.0,Fang Kong;Zilong Wang;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;John Hopcroft Center, Shanghai Jiao Tong University",PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96952,,,https://openreview.net/forum?id=07N0qoaZ2L,/media/PosterPDFs/NeurIPS%202024/96952.png?t=1731746661.9360106
5,14,-0.31746334,-0.03755091,4,-0.21275706367934288,-0.0031904620518618575,"[0.0031895192776291415, 3.6323736050542426e-13, 3.2991504881942696e-06, 2.524793570322809e-05, 0.9967819336358161]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,08A6X7FSTs,Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text,Text-to-3D Scene Generation;Latent Diffusion Models,5.5,4.5,Xinyang Li;Zhangyu Lai;Linning Xu;Yansong Qu;Liujuan Cao;Shengchuan Zhang;Bo Dai;Rongrong Ji,Xiamen University;Xiamen University;Xiamen University;Xiamen University;Xiamen University;Shanghai AI Laboratory;Xiamen University;The Chinese University of Hong Kong,PhD student;MS student;PhD student;Full Professor;Assistant Professor;Scientist;Full Professor;Ph.D. student,https://neurips.cc/virtual/2024/poster/96951,,,https://openreview.net/forum?id=08A6X7FSTs,/media/PosterPDFs/NeurIPS%202024/96951.png?t=1732593534.8700738
5,15,0.21572201,0.15297481,0,0.046218503789983885,0.004953785986959865,"[0.9995863585373789, 0.00035945449364069244, 4.906513303951638e-05, 4.830673365492367e-06, 2.911625754049563e-07]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,08GbdALmEs,Learning Versatile Skills with Curriculum Masking,reinforcement learning;unsupervised pretraining;masked prediction;curriculum learning,5.25,3.25,Yao Tang;Zhihui Xie;Zichuan Lin;Deheng Ye;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;Tencent AI Lab;Tencent;John Hopcroft Center, Shanghai Jiao Tong University",Undergrad student;MS student;Researcher;Principal Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96950,,,https://openreview.net/forum?id=08GbdALmEs,/media/PosterPDFs/NeurIPS%202024/96950.png?t=1733319308.3295946
5,16,-0.17784788,-0.16018736,0,0.046218503789983885,0.004953785986959865,"[0.3715932323098711, 1.5802556922840984e-06, 3.5346023903727414e-12, 0.260333754006941, 0.3680714334239611]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,08nbMTxazb,Chicks4FreeID: A Benchmark Dataset for Chicken Re-Identification,animal re-identification;chicken re-identification;chicken dataset;re-identification dataset;benchmark dataset;closed-set re-identification;computer vision;chicken instance segmentation;poultry;livestock,4.75,4.0,Daria Kern;Tobias Schiele;Ulrich Klauck;Winfred Ingabire,Glasgow Caledonian University;Hochschule Aalen;Glasgow Caledonian University,PhD student;Full Professor;Lecturer,,,,,
5,17,0.12485067,-0.17534988,3,-0.12286635144929052,-0.2829108388789275,"[0.20896974761570986, 0.2695814408763977, 7.547247495637344e-18, 0.5214483429348669, 4.685730255515082e-07]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,08oUnmtj8Q,FSEO: A Few-Shot Evolutionary Optimization Framework for Expensive Multi-Objective Optimization and Constrained Optimization,Expensive optimization;few-shot optimization;multi-objective optimization;constrained optimization;surrogate-assisted evolutionary optimization,4.5,3.5,Xunzhao Yu,,,,,,,
5,18,-0.045080878,-0.32160506,3,-0.12286635144929052,-0.2829108388789275,"[0.03069081363594216, 0.004282480028090055, 3.433436838483459e-24, 0.9650235368169465, 3.1695190212496157e-06]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,09RKw0vXjR,Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations,feature selection;sparse coding;dictionary learning;compressed sensing;iterative hard thresholding;pruning method,5.75,3.0,Yasutoshi Ida;Sekitoshi Kanai;Atsutoshi Kumagai;Tomoharu Iwata;Yasuhiro Fujiwara,NTT;NTT;NTT;NTT;NTT,Researcher;Researcher;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96949,,,https://openreview.net/forum?id=09RKw0vXjR,/media/PosterPDFs/NeurIPS%202024/96949.png?t=1733375377.8112724
5,19,-0.29219365,-0.1354431,4,-0.21275706367934288,-0.0031904620518618575,"[0.039050572276527494, 6.866248492921077e-10, 6.871691172763452e-10, 0.013346718034397456, 0.947602708315281]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,09nyBqSdUz,RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance,Consistent image generation;Diverse image generation;Improve temporal-consistency;Feature injection from multiple images,5.5,4.0,Jiaojiao Fan;Haotian Xue;Qinsheng Zhang;Yongxin Chen,Georgia Institute of Technology;Georgia Institute of Technology;Georgia Institute of Technology;NVIDIA,PhD student;PhD student;Associate Professor;Research Intern,https://neurips.cc/virtual/2024/poster/96948,,,https://openreview.net/forum?id=09nyBqSdUz,/media/PosterPDFs/NeurIPS%202024/96948.png?t=1731392354.7708242
5,20,0.22983314,0.005944166,0,0.046218503789983885,0.004953785986959865,"[0.8164296933034264, 0.17645502492421272, 2.0701484055947492e-10, 0.00711523283845985, 4.8726886088300895e-08]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0AumdfLzpK,A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations,Visual Reinforcement Learning;Generalization,6.0,4.0,Wonil Song;Hyesong Choi;Kwanghoon Sohn;Dongbo Min,Yonsei Univ.;Ewha Womans University;Yonsei University;Ewha Womans University,PhD student;PhD student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96947,,,https://openreview.net/forum?id=0AumdfLzpK,/media/PosterPDFs/NeurIPS%202024/96947.png?t=1732451612.1247888
5,21,-0.2313607,0.15489271,4,-0.21275706367934288,-0.0031904620518618575,"[0.00162666857911457, 1.0888394549485328e-15, 0.23207188123867414, 5.775331244309145e-10, 0.766301449604677]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0AwMciNShl,"Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality",Human evaluation;text-to-video models,5.25,4.0,Tianle Zhang;Langtian Ma;Yuchen Yan;Yuchen Zhang;Yue Yang;Ziyao Guo;Wenqi Shao;Kai Wang;Yang You;Yu Qiao;Ping Luo;Kaipeng Zhang,University of Electronic Science and Technology of China;Southern University of Science and Technology;The University of Nottingham Ningbo China;University of Electronic Science and Technology of China;Xidian University;Shanghai AI Laboratory;National University of Singapore;National University of Singapore;Shanghai AI Laboratory;The University of Hong Kong;Shanghai Jiaotong University,Undergrad student;Undergrad student;Undergrad student;Undergrad student;MS student;Researcher;PhD student;Professor;Researcher;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96946,,,https://openreview.net/forum?id=0AwMciNShl,/media/PosterPDFs/NeurIPS%202024/96946.png?t=1729079669.652648
5,22,0.44196302,-0.22339565,1,0.4007888716927687,-0.08240049330680303,"[5.752451040092103e-07, 0.9999434124870346, 1.703020030793511e-29, 5.6012267861445235e-05, 9.440129620954533e-23]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0C3bLHwjsY,Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions,Online Matching;Competitive Analysis;Fairness Maximization,6.25,3.0,Will Ma;Pan Xu,Columbia University;New Jersey Institute of Technology,Assistant Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96945,,,https://openreview.net/forum?id=0C3bLHwjsY,/media/PosterPDFs/NeurIPS%202024/96945.png?t=1731641014.5806563
5,23,0.31953293,-0.23248373,1,0.4007888716927687,-0.08240049330680303,"[6.095749107341335e-05, 0.9976917041793119, 9.695560312122383e-27, 0.002247338329614543, 1.2845659872009681e-16]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0DE1dLMW2b,Quantum algorithm for large-scale market equilibrium computation,market equilibrium computation;quantum algorithm,6.0,2.75,Po-Wei Huang;Patrick Rebentrost,Centre for Quantum Technologies;National University of Singapore,Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96944,,,https://openreview.net/forum?id=0DE1dLMW2b,/media/PosterPDFs/NeurIPS%202024/96944.png?t=1731426989.5298698
5,24,0.0025802255,-0.08199731,0,0.046218503789983885,0.004953785986959865,"[0.9271916490863059, 0.0003401970709920251, 4.6898243782519775e-11, 0.06584871760669637, 0.006619436189107451]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0EfUYVMrLv,Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment,non-stationary environments;continuous distribution shift;test-time adaptation;unlabeled data,6.666666666666667,4.0,Zhen-Yu Zhang;Zhiyu Xie;Huaxiu Yao;Masashi Sugiyama,"RIKEN;Stanford University;Department of Computer Science, University of North Carolina at Chapel Hill;The University of Tokyo",Postdoc;MS student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96943,,,https://openreview.net/forum?id=0EfUYVMrLv,/media/PosterPDFs/NeurIPS%202024/96943.png?t=1731687693.6296034
5,25,0.023439856,-0.079839304,0,0.046218503789983885,0.004953785986959865,"[0.9301657476035676, 0.00074747248958557, 2.9000316068409635e-11, 0.06647195307137589, 0.002614826806470675]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0G0VpMjKyV,Sketching for Distributed Deep Learning: A Sharper Analysis,sketching;distributed learning;federated learning;optimization,5.666666666666667,4.0,Mayank Shrivastava;Berivan Isik;Qiaobo Li;Sanmi Koyejo;Arindam Banerjee,"University of Illinois, Urbana Champaign;Stanford University;Department of Computer Science, University of Illinois at Urbana-Champaign;University of Illinois, Urbana Champaign;Google",MS student;PhD student;PhD student;Professor;Research Scientist,https://neurips.cc/virtual/2024/poster/96942,,,https://openreview.net/forum?id=0G0VpMjKyV,/media/PosterPDFs/NeurIPS%202024/96942.png?t=1733481266.9121125
5,26,-0.06371302,0.3954228,2,-0.09354076594739029,0.33204128402332034,"[1.938412572759394e-05, 1.1642286372058903e-19, 0.9999726476553977, 4.99748968379888e-19, 7.968218874724398e-06]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,0G5OK5vmmg,WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts,Benchmark;Large Language Models;Classical Chinese Literature and Language Arts,6.25,2.75,Jiahuan Cao;Yang Liu;Yongxin Shi;Kai Ding;Lianwen Jin,South China University of Technology;South China University of Technology;South China University of Technology;INTSIG Information;South China University of Technology,MS student;MS student;PhD student;Researcher;Professor,https://neurips.cc/virtual/2024/poster/97880,,,,/media/PosterPDFs/NeurIPS%202024/97880.png?t=1730896668.2191207
5,27,-0.2963673,0.015343715,4,-0.21275706367934288,-0.0031904620518618575,"[0.001904462784520637, 5.1582552776995674e-14, 9.240139605905221e-05, 1.3048911593012062e-06, 0.9980018309282094]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0G8AXwtmy2,T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition,harmful dataset;harmful content detection;Vision Language Model,6.5,3.75,Chen Yeh;You-Ming Chang;Wei-Chen Chiu;Ning Yu,National Yang Ming Chiao Tung University;National Yang Ming Chiao Tung University;National Chiao Tung University,MS student;MS student;Associate Professor,https://neurips.cc/virtual/2024/poster/97879,,,,/media/PosterPDFs/NeurIPS%202024/97879.png?t=1730218737.4487233
5,28,0.08612508,0.3898904,2,-0.09354076594739029,0.33204128402332034,"[0.002417813560259029, 2.7253357871097915e-14, 0.9975817495454304, 3.1342539697123505e-16, 4.368942832013621e-07]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,0Gl5WxY6es,Grounding Multimodal Large Language Models in Actions,Embodied AI;Multimodal Large Language Models;Reinforcement Learning;Imitation Learning,6.0,3.6666666666666665,Andrew Szot;Bogdan Mazoure;Harsh Agrawal;R Devon Hjelm;Zsolt Kira;Alexander T Toshev,Georgia Institute of Technology;Apple;Apple;Apple;Georgia Institute of Technology;Apple,PhD student;Research Scientist;Researcher;Researcher;Assistant Professor;research scientist,https://neurips.cc/virtual/2024/poster/96941,,,https://openreview.net/forum?id=0Gl5WxY6es,
5,29,-0.20296153,0.2345368,2,-0.09354076594739029,0.33204128402332034,"[0.00015803530082789702, 7.100467541558003e-18, 0.9610705725890931, 3.5774531942251913e-13, 0.03877139210972144]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,0Gmi8TkUC7,GenAI Arena: An Open Evaluation Platform for Generative Models,Evaluation;Benchmark;Platform;Generative Model,6.0,3.5,Dongfu Jiang;Max Ku;Tianle Li;Yuansheng Ni;Shizhuo Sun;Rongqi Fan;Wenhu Chen,Allen Institute for Artificial Intelligence;University of Waterloo;University of Waterloo;University of Toronto;NVIDIA;University of Waterloo,Intern;MS student;MS student;Undergrad student;Intern;Assistant Professor,https://neurips.cc/virtual/2024/poster/97878,,,,/media/PosterPDFs/NeurIPS%202024/97878.png?t=1730329031.3167162
5,30,-0.3021013,-0.23802479,3,-0.12286635144929052,-0.2829108388789275,"[0.10251469942037691, 5.588405721634893e-08, 2.0470252817852464e-14, 0.7381197726310329, 0.15936547206451246]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,0HRRNEAQFp,A General Protocol to Probe Large Vision Models for 3D Physical Understanding,3D physical scene understanding; Representation probing protocol; Benchmark and evaluation,6.333333333333333,4.0,Guanqi Zhan;Chuanxia Zheng;Weidi Xie;Andrew Zisserman,University of Oxford;University of Oxford;Shanghai Jiaotong University,PhD student;Postdoc;Associate Professor,https://neurips.cc/virtual/2024/poster/96940,,,https://openreview.net/forum?id=0HRRNEAQFp,/media/PosterPDFs/NeurIPS%202024/96940.png?t=1731705235.0575316
5,31,0.40233114,0.06031101,1,0.4007888716927687,-0.08240049330680303,"[0.017305108670103705, 0.9826174138602972, 8.850681748347897e-12, 7.74774607456677e-05, 2.867261106263428e-15]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0JSKjdePGq,When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL,reinforcement learning;continuous-time,6.75,3.25,Lenart Treven;Bhavya Sukhija;Yarden As;Florian Dorfler;Andreas Krause,"Swiss Federal Institute of Technology;ETHZ - ETH Zurich;Department of Computer Science, ETHZ - ETH Zurich;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96939,,,https://openreview.net/forum?id=0JSKjdePGq,/media/PosterPDFs/NeurIPS%202024/96939.png?t=1730197260.75527
5,32,-0.31179968,-0.050893012,4,-0.21275706367934288,-0.0031904620518618575,"[0.0045079354565860045, 1.1456485232171922e-12, 1.0272451612601733e-06, 6.27245480745857e-05, 0.9954283127490325]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0KseSacluJ,CoFie: Learning Compact Neural Surface Representations with Coordinate Fields,Neural Surface Representation;Shape Auto-Decoding;Coordinate Field.,5.0,4.0,Hanwen Jiang;Haitao Yang;Georgios Pavlakos;Qixing Huang,University of Texas at Austin;The University of Texas at Austin;University of Texas at Austin;University of Texas at Austin,PhD student;PhD student;Assistant Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96938,,,https://openreview.net/forum?id=0KseSacluJ,
5,33,0.11298243,0.035079706,0,0.046218503789983885,0.004953785986959865,"[0.9984743533191894, 0.0004591527279521284, 8.918180886573951e-08, 0.0009521069013682442, 0.00011429786968160467]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0KvYLaTBTE,Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference,Generative models;Reinforcement learning;Decision transformer,6.333333333333333,3.0,Deqian Kong;Dehong Xu;Minglu Zhao;Bo Pang;Jianwen Xie;Andrew Lizarraga;Yuhao Huang;Sirui Xie;Ying Nian Wu,"University of California, Los Angeles;Amazon;University of California, Los Angeles;University of California, Los Angeles;Xi'an Jiaotong University;University of California, Los Angeles;University of California, Los Angeles;UCLA",PhD student;Intern;PhD student;PhD student;PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96937,,,https://openreview.net/forum?id=0KvYLaTBTE,
5,34,-0.23456638,0.06657637,4,-0.21275706367934288,-0.0031904620518618575,"[0.0038488562624724772, 1.4361135951265992e-13, 0.0009841939787660608, 2.0163139216142286e-07, 0.9951667481272257]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0LXotew9Du,KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization,Quantization;KV Cache;LLM Inference;Compression;Long Context Length,6.25,3.25,Coleman Richard Charles Hooper;Sehoon Kim;Hiva Mohammadzadeh;Michael W. Mahoney;Sophia Shao;Kurt Keutzer;Amir Gholami,"University of California, Berkeley;University of California, Berkeley;University of California, Berkeley;University of California, Berkeley",PhD student;PhD student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96936,,,https://openreview.net/forum?id=0LXotew9Du,
5,35,0.11017645,-0.16371755,3,-0.12286635144929052,-0.2829108388789275,"[0.31602975283244783, 0.15594350117624467, 6.875627345472182e-17, 0.528024686358846, 2.0596324614724907e-06]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,0Lb8vZT1DB,Reliable Learning of Halfspaces under Gaussian Marginals,reliable learning;agnostic learning;halfspace;proper leaning;statistical query,7.25,2.25,Ilias Diakonikolas;Lisheng Ren;Nikos Zarifis,"University of Wisconsin - Madison;University of Wisconsin - Madison;University of Wisconsin, Madison",Full Professor;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96935,,,https://openreview.net/forum?id=0Lb8vZT1DB,
5,36,0.1429859,0.059452157,0,0.046218503789983885,0.004953785986959865,"[0.9989616700410752, 0.0006469906818752636, 2.88787749568845e-07, 0.0003674749199543368, 2.357556934563596e-05]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0LfgE6kvKZ,Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning,Federated Learning; Model Merging,5.0,3.6666666666666665,Minghui Chen;Meirui Jiang;Xin Zhang;Qi Dou;Zehua Wang;Xiaoxiao Li,"University of British Columbia;Meta Facebook;The Chinese University of Hong Kong;University of British Columbia;University of British Columbia;Department of Computer Science and Engineering, The Chinese University of Hong Kong",PhD student;Research Scientist;Assistant Professor;Researcher;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96934,,,https://openreview.net/forum?id=0LfgE6kvKZ,/media/PosterPDFs/NeurIPS%202024/96934.png?t=1731518093.5294044
5,37,-0.040502112,0.02318828,0,0.046218503789983885,0.004953785986959865,"[0.8198150587593295, 8.231828494955943e-07, 3.7605835434359972e-06, 0.000597484366560383, 0.17958287310771748]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0Lr9HQijA1,Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations,Imprecise Label Learning,5.75,3.0,Hao Chen;Ankit Shah;Jindong Wang;Ran Tao;Yidong Wang;Xiang Li;Xing Xie;Masashi Sugiyama;Rita Singh;Bhiksha Raj,"Carnegie Mellon University;Accenture;Microsoft Research;Peking University;Microsoft Research Asia;The University of Tokyo;School of Computer Science, Carnegie Mellon University;Mohamed bin Zayed University of Artificial Intelligence",PhD student;Principal Researcher;Researcher;PhD student;Senior Principal Researcher;Full Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96933,,,https://openreview.net/forum?id=0Lr9HQijA1,/media/PosterPDFs/NeurIPS%202024/96933.png?t=1731704880.9846606
5,38,-0.06471333,0.08954511,4,-0.21275706367934288,-0.0031904620518618575,"[0.4726112509314282, 9.93775550951501e-09, 0.0011622285631975723, 1.1215589345300479e-05, 0.5262152949782735]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0MXzbAv8xy,GFT: Graph Foundation Model with Transferable Tree Vocabulary,Graph Foundation Model;Transferability;Computation Tree;Graph Neural Network,6.0,3.75,Zehong Wang;Zheyuan Zhang;Nitesh V Chawla;Chuxu Zhang;Yanfang Ye,University of Notre Dame;University of Notre Dame;University of Notre Dame;University of Notre Dame,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96932,,,https://openreview.net/forum?id=0MXzbAv8xy,
5,39,0.06407858,0.09707585,0,0.046218503789983885,0.004953785986959865,"[0.9973010997453697, 4.32429650150407e-06, 6.14724180708721e-05, 3.1163559475519034e-05, 0.002601939980582392]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0NMzBwqaAJ,Not All Tokens Are What You Need for Pretraining,pre-training;next token prediction;data optimization;data selection,7.666666666666667,4.0,Zhenghao Lin;Zhibin Gou;Yeyun Gong;Xiao Liu;yelong shen;Ruochen Xu;Chen Lin;Yujiu Yang;Jian Jiao;Nan Duan;Weizhu Chen,Xiamen University;Microsoft;Microsoft Research Asia;Microsoft Research;Xiamen University;Tsinghua University;Microsoft;Microsoft Research Asia;Microsoft GenAI,MS student;Intern;Researcher;Researcher;Full Professor;Full Professor;Principal Researcher;Principal Researcher;Vice President,https://neurips.cc/virtual/2024/poster/96931,,,https://openreview.net/forum?id=0NMzBwqaAJ,/media/PosterPDFs/NeurIPS%202024/96931.png?t=1733724962.7310221
5,40,-0.021407472,0.09407413,0,0.046218503789983885,0.004953785986959865,"[0.8502000126852035, 9.768058605512225e-08, 0.0006654775250548269, 1.9237436918534195e-05, 0.1491151746722371]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0NQzQVu9tY,DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors,representation learning;offline reinforcement learning;behavioral cloning;visual distractor,7.0,3.0,Joseph Ortiz;Antoine Dedieu;Wolfgang Lehrach;J Swaroop Guntupalli;Carter Wendelken;Ahmad Humayun;Sivaramakrishnan Swaminathan;Guangyao Zhou;Miguel Lazaro-Gredilla;Kevin Patrick Murphy,Google DeepMind;Google DeepMind;Google Deepmind;Google DeepMind;Google;Google DeepMind;Google DeepMind;Google DeepMind;Google Deepmind;Google,Researcher;Researcher;Researcher;Researcher;Researcher;Researcher;Research Engineer;Research Scientist;Research Scientist;Principal Researcher,https://neurips.cc/virtual/2024/poster/97877,,,,/media/PosterPDFs/NeurIPS%202024/97877.png?t=1733266397.4133346
5,41,-0.056248758,0.025906589,0,0.046218503789983885,0.004953785986959865,"[0.6951317161639295, 3.181222444341379e-07, 7.005588395473365e-06, 0.00041939692860656, 0.30444156319682386]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0SMhqvgHST,EEVEE and GATE: Finding the right benchmarks and how to run them seamlessly,multi-modal;benchmarks;machine learning;model evaluation;benchmark frameworks,6.0,4.0,Antreas Antoniou;Eleni Triantafillou;Hugo Larochelle;Sebastien Montella;Fady Rezk;Kiyoon Kim;Linus Ericsson;Pavlos Vougiouklis;Justin Engelmann;Elliot J. Crowley;Srihari Humbarwadi;Yi Liu;Guang Yang;Jeff Z. Pan;Amos Storkey,"Google;Google;Huawei Technologies Ltd.;Samsung;Deargen;University of Edinburgh, University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh, University of Edinburgh;University of Edinburgh",Researcher;Research Scientist;Researcher;Intern;Researcher;Postdoc;Researcher;Assistant Professor;Researcher;Full Professor;Full Professor,,,,,
5,42,-0.15132618,0.02146309,4,-0.21275706367934288,-0.0031904620518618575,"[0.0673446011967665, 6.446131200536801e-10, 1.5304427045865343e-05, 3.8179174855928946e-05, 0.9326019145567186]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0SRJBtTNhX,IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors,Graph Machine Learning;Graph Data Augmentation;Graph Neural Networks,5.5,4.0,Shenghe Zheng;Hongzhi Wang;Xianglong Liu,Harbin Institute of Technology;Harbin Institute of Technology;Harbin Institute of Technology,MS student;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96930,,,https://openreview.net/forum?id=0SRJBtTNhX,/media/PosterPDFs/NeurIPS%202024/96930.png?t=1732617637.3891017
5,43,-0.18518934,0.0027779788,4,-0.21275706367934288,-0.0031904620518618575,"[0.03178806680564422, 1.608076738954709e-10, 5.251696033999822e-06, 4.0968883135797515e-05, 0.9681657124543782]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0T8xRFrScB,Benchmarking Counterfactual Image Generation,benchmark;causal inference;counterfactual image generation,7.25,3.75,Thomas Melistas;Nikos Spyrou;Nefeli Gkouti;Pedro Sanchez;Athanasios Vlontzos;Yannis Panagakis;Giorgos Papanastasiou;Sotirios A. Tsaftaris,"University of Athens;University of Athens;University of Athens;University of Edinburgh, University of Edinburgh;Spotify;Pfizer;University of Edinburgh",PhD student;PhD student;PhD student;PhD student;Researcher;Principal Researcher;Professor in machine learning and computer vision,https://neurips.cc/virtual/2024/poster/97876,,,,/media/PosterPDFs/NeurIPS%202024/97876.png?t=1731712408.6398222
5,44,0.5118622,-0.024860546,1,0.4007888716927687,-0.08240049330680303,"[8.309573030379872e-06, 0.9999860718374936, 2.3394029019950216e-19, 5.618589475964303e-06, 4.98265342377519e-23]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0TUMAAb3of,Queueing Matching Bandits with Preference Feedback,Bandits;Queue;Preference Feedback,6.0,2.5,Jung-hun Kim;Min-hwan Oh,Seoul National University;Seoul National University,Assistant Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96929,,,https://openreview.net/forum?id=0TUMAAb3of,/media/PosterPDFs/NeurIPS%202024/96929.png?t=1733803835.532587
5,45,-0.0018669573,0.3644946,2,-0.09354076594739029,0.33204128402332034,"[0.0004348059109278686, 2.7014216978865277e-16, 0.9995514802294112, 2.0420276059644116e-16, 1.3713859660500587e-05]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,0VeSCjRDBy,Adversarial Moment-Matching Distillation of Large Language Models,Knowledge distillation;Large language models;Imitation learning;Moment-matching;Adversarial training,6.25,3.0,Chen Jia,,,https://neurips.cc/virtual/2024/poster/96928,,,https://openreview.net/forum?id=0VeSCjRDBy,/media/PosterPDFs/NeurIPS%202024/96928.png?t=1731660620.7591212
5,46,-0.24925767,0.015651966,4,-0.21275706367934288,-0.0031904620518618575,"[0.005090899590146675, 9.904593910417922e-13, 3.476918430620109e-05, 3.409632609064823e-06, 0.9948709215919476]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0WCFI2Qx85,ScaleKD: Strong Vision Transformers Could Be Excellent Teachers,knowledge distillation;model compression;training acceleration;vision transformer;convolutional neural network;multi-layer perception,6.25,4.5,Jiawei Fan;Chao Li;Xiaolong Liu;Anbang Yao,Intel Labs China;Intel;Intel,Research Intern;Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96927,,,https://openreview.net/forum?id=0WCFI2Qx85,/media/PosterPDFs/NeurIPS%202024/96927.png?t=1731695837.2500114
5,47,0.2804453,-0.1894261,1,0.4007888716927687,-0.08240049330680303,"[0.0009508369852118422, 0.9894053929560593, 7.93103062247831e-23, 0.009643770058641048, 8.756784705081848e-14]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0XKvW4ijxp,Learning-Augmented Algorithms with Explicit Predictors,online algorithms;learning-augmented algorithms;scheduling;caching,6.0,4.0,Marek Elias;Haim Kaplan;Yishay Mansour;Shay Moran,"Bocconi University;Technion, Technion;School of Computer Science, Tel Aviv University",Assistant Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96926,,,https://openreview.net/forum?id=0XKvW4ijxp,/media/PosterPDFs/NeurIPS%202024/96926.png?t=1733319671.0065775
5,48,0.37225774,-0.11562894,1,0.4007888716927687,-0.08240049330680303,"[0.00019382046634974562, 0.9992241918063969, 7.891960980027909e-21, 0.0005819877272534142, 7.248189689260596e-17]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0XeNkkENuI,The Road Less Scheduled,Stochastic Optimization;Optimization;Convex Optimization;Learning Rates;Learning Rate Schedules,7.5,3.5,Aaron Defazio;Xingyu Alice Yang;Ahmed Khaled;Konstantin Mishchenko;Harsh Mehta;Ashok Cutkosky,Meta;Meta;Princeton University;Samsung;Google Research;Boston University,Research Scientist;Research Engineer;PhD student;Researcher;Software Engineer;Assistant Professor,https://neurips.cc/virtual/2024/poster/96925,,,https://openreview.net/forum?id=0XeNkkENuI,/media/PosterPDFs/NeurIPS%202024/96925.png?t=1730837481.9895687
5,49,0.1460578,0.21914145,0,0.046218503789983885,0.004953785986959865,"[0.9773451821174702, 8.069678557448447e-07, 0.022630761359900903, 4.602518742781164e-08, 2.3203529585955944e-05]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0ZZMUjZJYF,Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study,LLMs;Learning by Teaching;Reasoning;Mathematical Reasoning;Code Synthesis;Weak-to-Strong Generalization;In-Context Learning;Prompting;Knowledge Distillation;Education-Inspired,6.5,4.0,Xuefei Ning;Zifu Wang;Shiyao Li;Zinan Lin;Peiran Yao;Tianyu Fu;Matthew B. Blaschko;Guohao Dai;Huazhong Yang;Yu Wang,Tsinghua University;KU Leuven;Tsinghua University;Microsoft;Infinigence;Shanghai Jiaotong University;Tsinghua University;Tsinghua University;KU Leuven,Research Assistant Professor;PhD student;PhD student;Senior Researcher;Researcher;Associate Professor;Full Professor;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96924,,,https://openreview.net/forum?id=0ZZMUjZJYF,/media/PosterPDFs/NeurIPS%202024/96924.png?t=1732367562.4969194
5,50,0.07159563,-0.024327766,0,0.046218503789983885,0.004953785986959865,"[0.9885361629084969, 0.0007614823887861402, 1.4911240564935702e-09, 0.010123366175259678, 0.0005789870363331213]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0ZeONp33f0,Graph Neural Networks and Arithmetic Circuits,Machine Learning;Graph Neural Networks;Arithmetic Circuits;Computational Complexity,6.5,3.25,Timon Barlag;Vivian Holzapfel;Laura Strieker;Jonni Virtema;Heribert Vollmer,Universität Hannover;Leibniz Universität Hannover;Leibniz Universität Hannover;University of Sheffield;Leibniz Universität Hannover,PhD student;Undergrad student;PhD student;Lecturer;Full Professor,https://neurips.cc/virtual/2024/poster/96923,,,https://openreview.net/forum?id=0ZeONp33f0,/media/PosterPDFs/NeurIPS%202024/96923.png?t=1732106485.9402945
5,51,-0.078428976,-0.18954016,3,-0.12286635144929052,-0.2829108388789275,"[0.35370892979471985, 0.0002181836105789917, 2.4694376465996058e-15, 0.6393211382890247, 0.0067517483056739325]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,0aN7VWwp4g,Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting,Precipitation Nowcasting;Video Prediction;Fourier Analysis;Loss Function,6.0,4.0,Chiu-Wai Yan;Shi Quan Foo;Van-Hoan Trinh;Dit-Yan Yeung;Ka-Hing Wong;Wai-Kin Wong,Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology,Chair Professor;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96922,,,https://openreview.net/forum?id=0aN7VWwp4g,/media/PosterPDFs/NeurIPS%202024/96922.png?t=1731480203.951872
5,52,-0.23586994,0.37846398,2,-0.09354076594739029,0.33204128402332034,"[6.93217870683104e-08, 2.829921287176616e-25, 0.9999795206947957, 3.0603432132349267e-21, 2.0409983417358232e-05]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,0bFXbEMz8e,FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions,generative models;material generation;chemistry;flow matching;large language models,6.0,4.333333333333333,Anuroop Sriram;Benjamin Kurt Miller;Ricky T. Q. Chen;Brandon M Wood,"Meta Facebook;University of Amsterdam;FAIR at Meta;FAIR Labs, Meta AI",Principal Researcher;PhD student;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96921,,,https://openreview.net/forum?id=0bFXbEMz8e,/media/PosterPDFs/NeurIPS%202024/96921.png?t=1730973273.143089
5,53,-0.15925287,-0.015642455,4,-0.21275706367934288,-0.0031904620518618575,"[0.08610817558377538, 2.80801346526973e-09, 9.783897427009768e-07, 0.0002650657817215848, 0.913625777436747]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0bINeW40u4,Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning,Medical Multi-modal Alignment;Eye-gaze;Radiology,6.25,3.5,Chong Ma;Hanqi Jiang;Wenting Chen;Yiwei Li;Zihao Wu;Xiaowei Yu;Zhengliang Liu;Lei Guo;Dajiang Zhu;Tuo Zhang;Dinggang Shen;Tianming Liu;Xiang Li,"Northwest Polytechnical University Xi'an;Beijing Jiaotong University;City University of Hong Kong;University of Georgia;University of Georgia;University of Texas at Arlington, University of Texas at Arlington;University of Georgia;University of Texas at Arlington;Northwestern Polytechnical University;ShanghaiTech University;University of Georgia;Massachusetts General Hospital, Harvard University",PhD student;Undergrad student;PhD student;PhD student;PhD student;PhD student;PhD student;Assistant Professor;Associate Professor;Full Professor;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96920,,,https://openreview.net/forum?id=0bINeW40u4,
5,54,0.38273144,-0.19184409,1,0.4007888716927687,-0.08240049330680303,"[1.432024352202058e-05, 0.9996041370446855, 7.407177755732967e-26, 0.00038154271179246006, 5.937115526394548e-19]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0cSQ1Sg7db,Generalization of Hamiltonian algorithms,Generalization;stochastic algorithms;concentration inequalities;PAC-Bayes,6.5,3.0,Andreas Maurer,,,https://neurips.cc/virtual/2024/poster/96919,,,https://openreview.net/forum?id=0cSQ1Sg7db,
5,55,-0.029614072,-0.05991212,0,0.046218503789983885,0.004953785986959865,"[0.9341813847462993, 3.960701536229937e-05, 1.3184556205707107e-09, 0.025414578157557013, 0.040364428762325655]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0cgDDa4OFr,Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation,source distribution estimation;maximum entropy;Sliced-Wasserstein distance;empirical Bayes;simulation-based inference,5.8,2.8,Julius Vetter;Guy Moss;Cornelius Schröder;Richard Gao;Jakob H. Macke,Eberhard-Karls-Universität Tübingen;Eberhard-Karls-Universität Tübingen;University Tübingen;Eberhard-Karls-Universität Tübingen,PhD student;PhD student;Postdoc;Postdoc,https://neurips.cc/virtual/2024/poster/96918,,,https://openreview.net/forum?id=0cgDDa4OFr,/media/PosterPDFs/NeurIPS%202024/96918.png?t=1733318904.6928847
5,56,-0.041920777,-0.1336057,0,0.046218503789983885,0.004953785986959865,"[0.722487464855807, 0.00027597073100097666, 7.421852370725568e-13, 0.2645280050874047, 0.01270855932504541]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0d50Il6enG,Non-parametric classification via expand-and-sparsify representation,non-parametric regression;non-parametric classification;expand-and-sparsify representation;universal consistency;minimax-optimal convergence rate,6.0,3.0,Kaushik Sinha,Wichita State University,Associate Professor,https://neurips.cc/virtual/2024/poster/96917,,,https://openreview.net/forum?id=0d50Il6enG,/media/PosterPDFs/NeurIPS%202024/96917.png?t=1731697679.5420048
5,57,-0.05421332,-0.22073112,3,-0.12286635144929052,-0.2829108388789275,"[0.190558043136414, 0.0008586484000446438, 1.315499589624099e-17, 0.8079481123941115, 0.0006351960694300077]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,0dtA21q83C,DeNetDM: Debiasing by Network Depth Modulation,Trustworthy Machine Learning;Debiasing;Robustness,6.0,3.5,Silpa Vadakkeeveetil Sreelatha;Adarsh Kappiyath;Abhra Chaudhuri;Anjan Dutta,University of Surrey;University of Exeter;University of Surrey,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96916,,,https://openreview.net/forum?id=0dtA21q83C,/media/PosterPDFs/NeurIPS%202024/96916.png?t=1733689557.490417
5,58,-0.19589648,0.09422963,4,-0.21275706367934288,-0.0031904620518618575,"[0.008397557030127477, 4.704539644128777e-13, 0.0039038300787818583, 1.0517445212113455e-07, 0.9876985077161681]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0e5uOaJxo1,Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure,Graph Neural Network;Protein Sequence;Structure,5.0,3.3333333333333335,Bozhen Hu;Cheng Tan;Jun Xia;Yue Liu;Lirong Wu;Jiangbin Zheng;Yongjie Xu;Yufei Huang;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University, China;National University of Singapore;Westlake University;Westlake University;Westlake University;Zhejiang University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96915,,,https://openreview.net/forum?id=0e5uOaJxo1,/media/PosterPDFs/NeurIPS%202024/96915.png?t=1730385968.8958924
5,59,0.09615892,0.18102637,0,0.046218503789983885,0.004953785986959865,"[0.9906025640502784, 4.666929305170495e-07, 0.008879277383609739, 3.3021118415725807e-07, 0.0005173616619972905]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0feJEykDRx,Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models,spatial-temporal data mining;location-based service;check-in sequence;large language model,5.75,4.0,Letian Gong;Yan Lin;Xinyue Zhang;Yiwen Lu;Xuedi Han;Yichen Liu;Shengnan Guo;Youfang Lin;Huaiyu Wan,Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University,PhD student;PhD student;Undergrad student;Undergrad student;MS student;Associate Professor;Full Professor;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96914,,,https://openreview.net/forum?id=0feJEykDRx,/media/PosterPDFs/NeurIPS%202024/96914.png?t=1731289337.5941467
5,60,-0.013711061,-0.07216554,0,0.046218503789983885,0.004953785986959865,"[0.9399088201212326, 0.00012221129956692915, 2.251372159898943e-10, 0.0434329945078379, 0.016535973846225453]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0jld45XGgJ,Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?,neural collapse;deep neural collapse;unconstrained features model;deep unconstrained features model;low-rank bias,6.5,3.75,Peter Súkeník;Christoph H. Lampert;Marco Mondelli,Institute of Science and Technology;Institute of Science and Technology Austria;Institute of Science and Technology Austria,PhD student;Assistant Professor;Professor,https://neurips.cc/virtual/2024/poster/96913,,,https://openreview.net/forum?id=0jld45XGgJ,
5,61,0.49365819,-0.019841706,1,0.4007888716927687,-0.08240049330680303,"[2.1409146478720576e-05, 0.9999692073911062, 1.3565092029070766e-18, 9.383462415123797e-06, 7.230234501435678e-22]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0l9yGPTHAU,Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms,Robust Markov decision process;norm;sample complexity;strong duality,6.5,3.0,Pierre Clavier;Laixi Shi;Erwan Le Pennec;Eric Mazumdar;Adam Wierman;Matthieu Geist,"École Polytechnique;California Institute of Technology;Ecole polytechnique;Deparment of Computing + Mathematical Sciences, California Institute of Technology;California Institute of Technology;Google",PhD student;Postdoc;Full Professor;Assistant Professor;Professor;Researcher,https://neurips.cc/virtual/2024/poster/96912,,,https://openreview.net/forum?id=0l9yGPTHAU,
5,62,-0.096782275,0.2680031,2,-0.09354076594739029,0.33204128402332034,"[0.0013693837446036824, 1.4577780950454502e-15, 0.9914410674125967, 4.635447355284357e-13, 0.007189548842334551]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,0lBx844upd,ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models,network pruning;unstructured pruning;large language model;ADMM;pre-conditioned conjugate gradient;optimization,5.333333333333333,3.0,Xiang Meng;Kayhan Behdin;Haoyue Wang;Rahul Mazumder,Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology,PhD student;PhD student;PhD student;Associate Professor,https://neurips.cc/virtual/2024/poster/96911,,,https://openreview.net/forum?id=0lBx844upd,/media/PosterPDFs/NeurIPS%202024/96911.png?t=1731079283.0533488
5,63,-0.07022652,-0.30347943,3,-0.12286635144929052,-0.2829108388789275,"[0.041725502088541026, 0.0013263396642339731, 1.3727364061590584e-22, 0.9569279455660844, 2.0212681140682488e-05]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,0lau89u4oE,Accelerating Non-Maximum Suppression: A Graph Theory Perspective,non-maximum suppression;object detection;graph theory,5.5,3.25,King-Siong Si;Lu Sun;Weizhan Zhang;Tieliang Gong;Jiahao Wang;Jiang Liu;Hao Sun,Xi'an Jiaotong University;Xi'an Jiaotong University;North China University of Technology;China Telecom Corporation Ltd. Data&AI Technology Company,MS student;MS student;MS student;Researcher,https://neurips.cc/virtual/2024/poster/96910,,,https://openreview.net/forum?id=0lau89u4oE,/media/PosterPDFs/NeurIPS%202024/96910.png?t=1733315333.5240822
5,64,-0.08510746,-0.26066056,3,-0.12286635144929052,-0.2829108388789275,"[0.09040216612935763, 0.00043960693541834694, 1.3786467376384596e-19, 0.9088649792844522, 0.0002932476507717149]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,0m19blQT6y,BitsFusion: 1.99 bits Weight Quantization of Diffusion Model,Diffusion;Quantization;Stable Diffusion;Low bit,5.75,4.5,Yang Sui;Yanyu Li;Anil Kag;Yerlan Idelbayev;Junli Cao;Ju Hu;Dhritiman Sagar;Bo Yuan;Sergey Tulyakov;Jian Ren,Rutgers University;Northeastern University;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Rutgers University;Snap Inc.;Snap Inc.,PhD student;PhD student;Researcher;Researcher;Researcher;Researcher;Researcher;Assistant Professor;Director of Research;Research Scientist,https://neurips.cc/virtual/2024/poster/96909,,,https://openreview.net/forum?id=0m19blQT6y,/media/PosterPDFs/NeurIPS%202024/96909.png?t=1729915675.3170154
5,65,-0.00251228,0.3769304,2,-0.09354076594739029,0.33204128402332034,"[0.0002681462899108758, 8.339396964860362e-17, 0.999724366934585, 4.697905018782084e-17, 7.486775504134455e-06]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,0mRouJElbZ,ProgressGym: Alignment with a Millennium of Moral Progress,Progress Alignment;AI Alignment;Large Language Models,7.666666666666667,2.6666666666666665,Tianyi Qiu;Yang Zhang;Xuchuan Huang;Jasmine Xinze Li;Jiaming Ji;Yaodong Yang,"University of California, Berkeley;Peking University;Peking University;Peking University;Peking University;Peking University",Intern;Undergrad student;Undergrad student;Intern;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/97875,,,,/media/PosterPDFs/NeurIPS%202024/97875.png?t=1731742041.9348912
5,66,0.42614552,0.08994585,1,0.4007888716927687,-0.08240049330680303,"[0.01756384514922946, 0.9824108399973951, 6.324357070878563e-11, 2.5314790131479334e-05, 4.0277415305104525e-16]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0nSY8NiILP,Tight Bounds for Learning RUMs from Small Slates,discrete choice;random utility model;approximation theory,6.0,2.75,Flavio Chierichetti;Mirko Giacchini;Ravi Kumar;Alessandro Panconesi;Andrew Tomkins,Sapienza University of Rome;Sapienza University of Rome;Google;Sapienza University of Rome;Google,Full Professor;PhD student;Research Scientist;Full Professor;Researcher,https://neurips.cc/virtual/2024/poster/96908,,,https://openreview.net/forum?id=0nSY8NiILP,/media/PosterPDFs/NeurIPS%202024/96908.png?t=1732698791.0319488
5,67,0.25132486,-0.20319358,1,0.4007888716927687,-0.08240049330680303,"[0.0020383148047927874, 0.9748875030658448, 7.040147737682435e-23, 0.023074182128340465, 1.021897323455092e-12]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0nzKznCjFG,Private and Personalized Frequency Estimation in a Federated Setting,federated learning;personalization;privacy,5.75,3.0,Amrith Setlur;Vitaly Feldman;Kunal Talwar,Carnegie Mellon University;Apple AI Research;Apple,PhD student;Research Scientist;Research Scientist,https://neurips.cc/virtual/2024/poster/96907,,,https://openreview.net/forum?id=0nzKznCjFG,
5,68,-0.18157998,0.03947093,4,-0.21275706367934288,-0.0031904620518618575,"[0.022073808295259907, 2.673870061645121e-11, 7.47921653611403e-05, 4.933407851809386e-06, 0.9778464661047884]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0o7Rd5jngV,Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling,Transformer;expressive power;theoretical insights,6.333333333333333,3.0,Mingze Wang;Weinan E,Peking University;Peking University,PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96906,,,https://openreview.net/forum?id=0o7Rd5jngV,
5,69,-0.12251995,-0.049827244,4,-0.21275706367934288,-0.0031904620518618575,"[0.35120313412965304, 2.1213320996208557e-07, 3.9074407541961674e-08, 0.004944685141406516, 0.643851929521323]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0o9E8AsFgW,DarkSAM: Fooling Segment Anything Model to Segment Nothing,Segment Anything Model;Adversarial Example,6.333333333333333,4.0,Ziqi Zhou;Yufei Song;Minghui Li;Shengshan Hu;Xianlong Wang;Leo Yu Zhang;Dezhong Yao;Hai Jin,Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Griffith University;Huazhong University of Science and Technology;Huazhong University of Science and Technology,PhD student;PhD student;Assistant Professor;Associate Professor;PhD student;Researcher;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96905,,,https://openreview.net/forum?id=0o9E8AsFgW,
5,70,-0.18423451,0.25213403,2,-0.09354076594739029,0.33204128402332034,"[0.00012733910302681342, 5.4514214646249614e-18, 0.9829365621802861, 9.122227901767772e-14, 0.01693609871659599]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,0oUutV92YF,ProtGO: Function-Guided Protein Modeling for Unified Representation Learning,Teacher-student;Knowledge Distillation;Protein Function,5.666666666666667,3.6666666666666665,Bozhen Hu;Cheng Tan;Yongjie Xu;Zhangyang Gao;Jun Xia;Lirong Wu;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University;Westlake University, China;Westlake University, China;Westlake University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96904,,,https://openreview.net/forum?id=0oUutV92YF,/media/PosterPDFs/NeurIPS%202024/96904.png?t=1730386167.5899446
5,71,-0.04843812,0.4040603,2,-0.09354076594739029,0.33204128402332034,"[2.4194715081712555e-05, 1.8889222465621027e-19, 0.9999714242235358, 3.4004918202161065e-19, 4.381061382425863e-06]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,0og7nmvDbe,Confidence Regulation Neurons in Language Models,LLMs;Interpretability;Mechanistic Interpretability,7.0,3.75,Alessandro Stolfo;Ben Peng Wu;Wes Gurnee;Yonatan Belinkov;Xingyi Song;Mrinmaya Sachan;Neel Nanda,"ETHZ - ETH Zurich;University of Sheffield;Massachusetts Institute of Technology;Technion, Technion;University of Sheffield;Google DeepMind;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Assistant Professor;Lecturer;Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96903,,,https://openreview.net/forum?id=0og7nmvDbe,
5,72,0.25011468,-0.18353273,1,0.4007888716927687,-0.08240049330680303,"[0.0037638661439153053, 0.9701972285064305, 1.4075475713014354e-21, 0.026038905346492072, 3.1619629966693497e-12]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0qb8KoPsej,Accelerating Matroid Optimization through Fast Imprecise Oracles,matroid optimization;weak-strong models;learning-augmented algorithms;algorithms with predictions;query minimization;robustness,5.5,2.75,Franziska Eberle;Felix Hommelsheim;Alexander Lindermayr;Zhenwei Liu;Nicole Megow;Jens Schlöter,Technische Universität Berlin;Universität Bremen;Universität Bremen;Universität Bremen;Universität Bremen,Postdoc;Postdoc;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96902,,,https://openreview.net/forum?id=0qb8KoPsej,
5,73,0.24778247,-0.18444899,1,0.4007888716927687,-0.08240049330680303,"[0.004016841718373442, 0.9680288702506725, 1.435384623987273e-21, 0.027954288027083905, 3.870200190252765e-12]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0rl5vWOzRU,Score-Optimal Diffusion Schedules,Diffusion model;adaptive schedule;Annealed Langevin,6.0,3.0,Christopher Williams;Andrew Campbell;Arnaud Doucet;Saifuddin Syed,University of Oxford;University of Oxford;University of Oxford;University of Oxford,PhD student;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96901,,,https://openreview.net/forum?id=0rl5vWOzRU,
5,74,-0.17648138,-0.41862112,3,-0.12286635144929052,-0.2829108388789275,"[0.010334477821223771, 0.000170045773502246, 2.0006504265365e-28, 0.9894938654290101, 1.610976263953744e-06]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,0sJBW05a2W,3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration,Point Cloud Registration;Focus and Matching,5.666666666666667,4.333333333333333,Liyuan Zhang;Le Hui;qi liu;Bo Li;Yuchao Dai,Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwestern Polytechnical University Xi'an;Northwestern Polytechnical University,MS student;Associate Professor;Researcher;Associate Professor;Professor,https://neurips.cc/virtual/2024/poster/96900,,,https://openreview.net/forum?id=0sJBW05a2W,/media/PosterPDFs/NeurIPS%202024/96900.png?t=1731333373.8074756
5,75,-0.16704087,-0.3598848,3,-0.12286635144929052,-0.2829108388789275,"[0.01841877446092766, 8.223810034648386e-05, 1.205546930704458e-24, 0.9814748593502948, 2.4128088431069677e-05]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,0sycTGl4In,4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization,Dynamic Novel View Synthesis;4D Gaussian splatting;Sparse reconstruction;in-the-wild,5.333333333333333,4.666666666666667,Mijeong Kim;Jongwoo Lim;Bohyung Han,Seoul National University;Seoul National University,Full Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96899,,,https://openreview.net/forum?id=0sycTGl4In,/media/PosterPDFs/NeurIPS%202024/96899.png?t=1733712090.5881364
5,76,0.61073065,0.018717432,1,0.4007888716927687,-0.08240049330680303,"[4.3104157782244123e-07, 0.9999993556723487, 1.5105798586703486e-19, 2.1328607350052188e-07, 1.940529749024658e-28]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,0uGlKYS7a2,Maximizing utility in multi-agent environments by anticipating the behavior of other learners,Game Theory; no regret; learning theory;,5.5,3.25,Angelos Assos;Yuval Dagan;Constantinos Costis Daskalakis,Massachusetts Institute of Technology;Massachusetts Institute of Technology,MS student;Full Professor,https://neurips.cc/virtual/2024/poster/96898,,,https://openreview.net/forum?id=0uGlKYS7a2,/media/PosterPDFs/NeurIPS%202024/96898.png?t=1731753379.9098587
5,77,-0.07488669,0.3827278,2,-0.09354076594739029,0.33204128402332034,"[2.0578315508545066e-05, 1.44824791005581e-19, 0.9999630416889246, 1.3843840921657103e-18, 1.6379995566952073e-05]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,0uXtFk5KNJ,BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models,block coordinate descent;large language models,5.25,3.75,Qijun Luo;Hengxu Yu;Xiao Li,"The Chinese University of Hong Kong, Shenzhen;The Chinese University of Hong Kong, Shenzhen;Chinese University of Hong Kong Shen Zhen",PhD student;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96897,,,https://openreview.net/forum?id=0uXtFk5KNJ,/media/PosterPDFs/NeurIPS%202024/96897.png?t=1733743857.9232197
5,78,0.022653038,0.24370801,2,-0.09354076594739029,0.33204128402332034,"[0.21179826698052792, 1.869794287159544e-10, 0.7830836248847585, 7.638756763700199e-10, 0.005118107183858346]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,0zFVhMBZHJ,Mixture of Tokens: Continuous MoE through Cross-Example Aggregation,LLM;Mixture of Experts;MoE;conditional computation;fully-differentiable;language modeling,6.0,3.6666666666666665,Szymon Antoniak;Michał Krutul;Maciej Pióro;Jakub Krajewski;Jan Ludziejewski;Kamil Ciebiera;Krystian Król;Tomasz Odrzygóźdź;Marek Cygan;Sebastian Jaszczur,IDEAS NCBR Sp.;IDEAS NCBR Sp.;University of Warsaw;University of Warsaw;IDEAS NCBR Sp.;University of Warsaw;IDEAS NCBR;Nomagic;University of Warsaw,PhD student;Researcher;PhD student;PhD student;Intern;MS student;Postdoc;Founder / CTO;PhD student,https://neurips.cc/virtual/2024/poster/96896,,,https://openreview.net/forum?id=0zFVhMBZHJ,/media/PosterPDFs/NeurIPS%202024/96896.png?t=1730308223.324062
5,79,0.24368975,0.18879418,0,0.046218503789983885,0.004953785986959865,"[0.999450778559213, 0.0002803687178676786, 0.00026803162429234434, 7.824834079239701e-07, 3.861521899129125e-08]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,0zWzJj6lO3,Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents,cooperative AI;AI safety;LLM agents;cognitive science;language model evaluation;dynamic evaluation;alignment;agency;evolving benchmarks;multi-agent interactions,5.75,3.5,Giorgio Piatti;Zhijing Jin;Max Kleiman-Weiner;Bernhard Schölkopf;Mrinmaya Sachan;Rada Mihalcea,Common Sense Machines;University of Michigan;Swiss Federal Institute of Technology,Principal Researcher;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96895,,,https://openreview.net/forum?id=0zWzJj6lO3,
5,80,-0.16938657,-0.05973538,4,-0.21275706367934288,-0.0031904620518618575,"[0.126411437231009, 1.6281051541224856e-08, 3.2753153347658064e-08, 0.0024775002095240913, 0.871111013525262]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,0zfUiSX5si,AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases,De Novo Peptide sequencing;Proteomics;Mass Spectrum,5.333333333333333,3.0,Jun Xia;Shaorong Chen;Jingbo Zhou;Xiaojun Shan;Wenjie Du;Zhangyang Gao;Cheng Tan;Bozhen Hu;Jiangbin Zheng;Stan Z. Li,"Westlake University, China;Westlake University;Jilin University;University of Electronic Science and Technology of China;University of Science and Technology of China;Westlake University, China;Zhejiang University & Westlake University;Westlake University;Westlake University;Westlake University",PhD student;PhD student;Undergrad student;Undergrad student;Assistant Professor;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96894,,,https://openreview.net/forum?id=0zfUiSX5si,
5,81,-0.25151917,-0.28693447,3,-0.12286635144929052,-0.2829108388789275,"[0.04974595875215846, 9.901589919656011e-07, 2.2373959648856026e-18, 0.9438769582665935, 0.006376092822256031]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,105ZuvpdyW,SegVol: Universal and Interactive Volumetric Medical Image Segmentation,Volumetric Medical Image Segmentation;3D Segmentation Foundation Model;Universal and Interactive 3D Segmentation,7.666666666666667,4.333333333333333,Yuxin Du;Fan BAI;Tiejun Huang;Bo Zhao,Beijing Academy of Artificial Intelligence;The Chinese University of Hong Kong;Peking University;BAAI,Intern;PhD student;Full Professor;Principal Researcher,https://neurips.cc/virtual/2024/poster/96893,,,https://openreview.net/forum?id=105ZuvpdyW,/media/PosterPDFs/NeurIPS%202024/96893.png?t=1731410503.871179
5,82,0.04577409,-0.24324691,3,-0.12286635144929052,-0.2829108388789275,"[0.09337526792612814, 0.04248650571793548, 1.1837707704608243e-20, 0.8641359764819172, 2.2498740192414846e-06]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,1067784F6e,Data Distribution Valuation,Data distribution valuation;Huber model;Maximum mean discrepancy,6.333333333333333,4.333333333333333,Xinyi Xu;Shuaiqi Wang;Chuan-Sheng Foo;Bryan Kian Hsiang Low;Giulia Fanti,"National University of Singapore;Carnegie Mellon University;Institute for Infocomm Research, A*STAR;National University of Singapore;Carnegie Mellon University",PhD student;PhD student;Principal Scientist;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96892,,,https://openreview.net/forum?id=1067784F6e,/media/PosterPDFs/NeurIPS%202024/96892.png?t=1731176029.7581189
5,83,-0.22563006,-0.049784996,4,-0.21275706367934288,-0.0031904620518618575,"[0.025518203213869918, 2.1532290680074022e-10, 1.6675131007143642e-07, 0.0003215208561008268, 0.9741601089633963]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,12A1RT1L87,Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?,Dataset Condensation;Dataset Distillation,5.666666666666667,3.6666666666666665,Lingao Xiao;Yang He,"School of Computer Science and  Engineering, Nanyang Technological University;Institute of High Performance Computing, Singapore, A*STAR",Undergrad student;Researcher,https://neurips.cc/virtual/2024/poster/96891,,,https://openreview.net/forum?id=12A1RT1L87,/media/PosterPDFs/NeurIPS%202024/96891.png?t=1731138766.8349779
5,84,-0.20074943,0.040258985,4,-0.21275706367934288,-0.0031904620518618575,"[0.012676563818555111, 6.5446197939197285e-12, 9.77429739814886e-05, 2.6490923750383373e-06, 0.9872230441085436]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,135eKqDoRR,Bayesian-guided Label Mapping for Visual Reprogramming,visual reprogramming;adversarial reprogramming;output label mapping;Bayesian probability,7.25,4.0,Chengyi Cai;Zesheng Ye;Lei Feng;Jianzhong Qi;Feng Liu,University of Melbourne;Singapore University of Technology and Design;University of Melbourne;University of Melbourne,PhD student;Assistant Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96890,,,https://openreview.net/forum?id=135eKqDoRR,
5,85,-0.1496939,0.30529067,2,-0.09354076594739029,0.33204128402332034,"[3.3878453137528676e-05, 4.459143319489033e-19, 0.9988612625950749, 6.124583527047184e-16, 0.0011048589517869297]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,14hLJr6kZ3,Enhancing Domain Adaptation through Prompt Gradient Alignment,transfer learning; domain adaptation; prompt-tuning,6.25,3.25,Hoang Phan;Tung Lam Tran;Quyen Tran;Trung Le,VinAi Research;VinAI Research;Monash University;New York University,Research resident;Research Resident;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96889,,,https://openreview.net/forum?id=14hLJr6kZ3,/media/PosterPDFs/NeurIPS%202024/96889.png?t=1732036918.0147438
5,86,0.2630342,0.051892787,0,0.046218503789983885,0.004953785986959865,"[0.8561198077109042, 0.14261849138747684, 5.187582421471969e-09, 0.0012616886106957379, 7.103341049043111e-09]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,15460JjocO,Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners,multi-agent;reinforcement learning;robustness;diversity;specialization,7.0,3.6666666666666665,Rujikorn Charakorn;Poramate Manoonpong;Nat Dilokthanakul,Sakana AI;Vidyasirimedhi Institute of Science and Technology;King Mongkut's Institute of Technology Ladkrabang,Intern;Full Professor;Lecturer,https://neurips.cc/virtual/2024/poster/96888,,,https://openreview.net/forum?id=15460JjocO,/media/PosterPDFs/NeurIPS%202024/96888.png?t=1731395258.7214391
5,87,0.61719507,-0.024593957,1,0.4007888716927687,-0.08240049330680303,"[8.649462713997845e-08, 0.9999996530364026, 4.626925954381852e-22, 2.604689701270223e-07, 1.6082520600485832e-29]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,15Jm9v7wCo,No-Regret Learning for Fair Multi-Agent Social Welfare Optimization,Online Learning;Nash Social Welfare,5.666666666666667,3.3333333333333335,Mengxiao Zhang;Ramiro Deo-Campo Vuong;Haipeng Luo,University of Southern California;University of Southern California,Undergrad student;Associate Professor,https://neurips.cc/virtual/2024/poster/96887,,,https://openreview.net/forum?id=15Jm9v7wCo,
5,88,-0.14552048,-0.15470643,0,0.046218503789983885,0.004953785986959865,"[0.4903721221245826, 6.197086332808586e-06, 2.3851450359121195e-12, 0.29372005127822104, 0.2159016295084786]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,15PS30UOUp,Kuro Siwo: 33 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping,Synthetic Aperture Radar;SAR;Deep Learning;Remote Sensing;Floods;dataset,6.75,3.75,Nikolaos Ioannis Bountos;Maria Sdraka;Angelos Zavras;Andreas Karavias;Ilektra Karasante;Themistocles Herekakis;Angeliki Thanasou;Dimitrios Michail;Ioannis Papoutsis,National Observatory of Athens;National Observatory of Athens;Harokopio University;The Centre for Research & Technology;National Observatory of Athens ;National Observatoty of Athens;National Observatory of Athens;Harokopio University;National Technical University of Athens,PhD student;Researcher;PhD student;Researcher;Researcher;Researcher;Researcher;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97874,,,,
5,89,0.004352061,-0.07103703,0,0.046218503789983885,0.004953785986959865,"[0.9472279570884551, 0.0002497620939450408, 1.3690419893269693e-10, 0.04497996850493105, 0.007542312175764585]","[0.014898668583552021, 0.015048253132221853]",0.22789447786063988,164QnJsYjF,Dense Associative Memory Through the Lens of Random Features,Associative Memory;Kernels;Random Features;Hopfield Network,6.0,3.0,Benjamin Hoover;Duen Horng Chau;Hendrik Strobelt;Parikshit Ram;Dmitry Krotov,International Business Machines;International Business Machines;International Business Machines;Massachusetts Institute of Technology;Georgia Institute of Technology,AI Research Engineer;Principal Researcher;Principal Researcher;Researcher;Full Professor,https://neurips.cc/virtual/2024/poster/96886,,,https://openreview.net/forum?id=164QnJsYjF,/media/PosterPDFs/NeurIPS%202024/96886.png?t=1733846086.053208
5,90,-0.31772932,0.41427824,2,-0.09354076594739029,0.33204128402332034,"[8.342919583066602e-10, 8.536190157360713e-30, 0.9999986736582475, 1.4817286942776214e-24, 1.3255074606632325e-06]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,168NLzTpw8,Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation,Vision-Language;Region-Level Understanding;Multimodal Large Language Model,5.75,3.75,Yaoyuan Liang;Zhuojun Cai;Jian Xu;Guanbo Huang;Yiran Wang;Xiao Liang;Jiahao Liu;Ziran Li;Jingang Wang;Shao-Lun Huang,"Tsinghua Shenzhen International Graduate School, Tsinghua University;Microsoft;University of Electronic Science and Technology of China;Tsinghua University;Tsinghua University;Meituan;Meituan;Tsinghua University",PhD student;Intern;Undergrad student;MS student;MS student;Researcher;Researcher;Associate Professor,https://neurips.cc/virtual/2024/poster/96885,,,https://openreview.net/forum?id=168NLzTpw8,
5,91,-0.118134014,0.26676714,2,-0.09354076594739029,0.33204128402332034,"[0.0006840578377058705, 2.891199003274188e-16, 0.9909213355659564, 2.2831853196233376e-13, 0.008394606596109152]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,181llen2gw,A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks,Vision-Language Model;Fairness;Debias,6.333333333333333,3.6666666666666665,Hoin Jung;Taeuk Jang;Xiaoqian Wang,Purdue University;Purdue University;Purdue University,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96884,,,https://openreview.net/forum?id=181llen2gw,/media/PosterPDFs/NeurIPS%202024/96884.png?t=1731379505.2628894
5,92,-0.19037005,0.30377576,2,-0.09354076594739029,0.33204128402332034,"[7.993242106645048e-06, 1.712025981263874e-20, 0.9989372897473207, 1.3790317301594743e-16, 0.0010547170105722928]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,18FGRNd0wZ,Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation,tokenization of crystals;language models;materials generation,6.0,3.5,Keqiang Yan;Xiner Li;Hongyi Ling;Kenna Ashen;Carl Edwards;Raymundo Arroyave;Marinka Zitnik;Heng Ji;Xiaofeng Qian;Xiaoning Qian;Shuiwang Ji,"Texas A&M University;Texas A&M University - College Station;Texas A&M University - College Station;Texas A&M University - College Station;Genentech;Texas A&M University Main Campus;Harvard University;University of Illinois, Urbana-Champaign;Texas A&M University;Texas A&M;Texas A&M University",PhD student;PhD student;PhD student;PhD student;Intern;Assistant Professor;Full Professor;Associate Professor;Full Professor;Professor,https://neurips.cc/virtual/2024/poster/96883,,,https://openreview.net/forum?id=18FGRNd0wZ,/media/PosterPDFs/NeurIPS%202024/96883.png?t=1733428872.6393995
5,93,-0.18803668,0.09546091,4,-0.21275706367934288,-0.0031904620518618575,"[0.010462188215971658, 7.796069038014448e-13, 0.0039238865574562866, 1.243047476528627e-07, 0.9856138009210449]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,18RdkSv9h9,FINALLY: fast and universal speech enhancement with studio-like quality,speech enhancement; generative models,6.5,4.75,Nicholas Babaev;Kirill Tamogashev;Azat Saginbaev;Ivan Shchekotov;Hanbin Bae;Hosang Sung;WonJun Lee;Hoon-Young Cho;Pavel Andreev,"Samsung;Skolkovo Institute of Science and Technology;Moscow Institute of Physics and Technology;Samsung;Samsung;Samsung;Higher School of Economics, Higher School of Economics",Researcher;MS student;MS student;Principal Researcher;Researcher;Vice President;MS student,https://neurips.cc/virtual/2024/poster/96882,,,https://openreview.net/forum?id=18RdkSv9h9,/media/PosterPDFs/NeurIPS%202024/96882.png?t=1731683595.700073
5,94,0.32727078,-0.11709024,1,0.4007888716927687,-0.08240049330680303,"[0.0012009796196227524, 0.9963681387821547, 1.1913544682447836e-19, 0.002430881598208071, 1.430158641473766e-14]","[0.016681731001044708, 0.012186618506419883]",0.18894708077409159,1ATLLgvURu,Learning-Augmented Priority Queues,learning-augmented algorithms;algorithms with predictions;priority queue;shortest paths;Dijkstra,5.75,4.25,Ziyad Benomar;Christian Coester,University of Oxford,Associate Professor,https://neurips.cc/virtual/2024/poster/96881,,,https://openreview.net/forum?id=1ATLLgvURu,
5,95,0.3095995,0.5030761,2,-0.09354076594739029,0.33204128402332034,"[0.026204486577204235, 4.712172565030532e-11, 0.973795513375597, 3.1660992255351766e-18, 7.706556038640193e-14]","[0.018580429468261453, 0.005464061771551785]",0.18968688989988752,1BZKqZphsW,Risk-Averse Fine-tuning of Large Language Models,Risk Averse Reinforcement Learning;Large Language Model Finetuning,5.8,3.2,Sapana Chaudhary;Ujwal Dinesha;Dileep Kalathil;Srinivas Shakkottai,Texas A&M University;Texas A&M University - College Station;Texas A&M University;Texas A&M,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96880,,,https://openreview.net/forum?id=1BZKqZphsW,/media/PosterPDFs/NeurIPS%202024/96880.png?t=1733328781.5713553
5,96,-0.26364937,-0.38828564,3,-0.12286635144929052,-0.2829108388789275,"[0.010824588412437901, 3.248206335160216e-06, 7.651506962712515e-25, 0.9891352100640007, 3.6953317226097885e-05]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,1CssOqRYyz,Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds,compression;point cloud;diffusion,4.0,4.0,Kai Liu;Kang You;Pan Gao,"Nanjing University of Aeronautics and Astronautics;Nanjing university;Nanjing University of Aeronautics and Astronautics, Tsinghua University",MS student;PhD student;Associate Professor,,,,,
5,97,-0.25224024,-0.31188005,3,-0.12286635144929052,-0.2829108388789275,"[0.03190026753622706, 1.39016869225625e-06, 5.545828364797878e-20, 0.9663809048617739, 0.0017174374333068204]","[0.016211104609221115, 0.007147525561211498]",0.1690550213939759,1Du3mMP5YN,Learning to Shape In-distribution Feature Space for Out-of-distribution Detection,Out-of-distribution Detection,5.75,4.0,Yonggang Zhang;Jie Lu;Bo Peng;Zhen Fang;Yiu-ming Cheung,Hong Kong Baptist University;University of Technology Sydney;University of Technology Sydney,Postdoc;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96879,,,https://openreview.net/forum?id=1Du3mMP5YN,/media/PosterPDFs/NeurIPS%202024/96879.png?t=1731745181.7993424
5,98,-0.30068702,-0.14781809,4,-0.21275706367934288,-0.0031904620518618575,"[0.04545566763270633, 9.223697571627226e-10, 3.02028442312512e-10, 0.023935157985596946, 0.9306091731572984]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,1ELFGSNBGC,Multiview Scene Graph,scene representation; spatial understanding; place recognition; object correspondence; scene graph,5.25,3.25,Juexiao Zhang;Gao Zhu;Sihang Li;Xinhao Liu;Haorui Song;Xinran Tang;Chen Feng,New York University;New York University;New York University;New York University;New York University;New York University;New York University,PhD student;MS student;PhD student;PhD student;MS student;MS student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96878,,,https://openreview.net/forum?id=1ELFGSNBGC,/media/PosterPDFs/NeurIPS%202024/96878.png?t=1731728482.5838113
5,99,-0.09486352,0.005280091,4,-0.21275706367934288,-0.0031904620518618575,"[0.3901772604361469, 8.090957837831897e-08, 2.5863715755741704e-06, 0.0005409760888366501, 0.6092790961938626]","[0.0054719864890693274, 0.0063598164580718815]",0.22441653007140522,1F32iCJFfa,Schrodinger Bridge Flow for Unpaired Data Translation,unpaired data translation;diffusion models;Schrodinger bridge;bridge matching;stochastic interpolant;flow matching,6.5,4.0,Valentin De Bortoli;Iryna Korshunova;Andriy Mnih;Arnaud Doucet,University of Oxford;Google DeepMind;Google DeepMind;University of Oxford,Postdoc;Researcher;Research Scientist;Full Professor,https://neurips.cc/virtual/2024/poster/96877,,,https://openreview.net/forum?id=1F32iCJFfa,/media/PosterPDFs/NeurIPS%202024/96877.png?t=1731688420.732189
6,0,0.08799766,-0.06060414,0,0.043912488447873634,0.0009302794543285151,"[0.9683409833764014, 0.0034361592313366875, 1.4189739285128863e-11, 0.028059874018124337, 0.00016298335994776418]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,00Sx577BT3,The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning,numerical simulations;fluid-dynamics;partial differential equations;operator learning,6.666666666666667,3.6666666666666665,Ruben Ohana;Michael McCabe;Lucas Thibaut Meyer;Rudy Morel;Fruzsina Julia Agocs;Miguel Beneitez;Marsha Berger;Blakesley Burkhart;Stuart B. Dalziel;Drummond Buschman Fielding;Daniel Fortunato;Jared A. Goldberg;Keiya Hirashima;Yan-Fei Jiang;Rich Kerswell;Suryanarayana Maddu;Jonah M. Miller;Payel Mukhopadhyay;Stefan S. Nixon;Jeff Shen;Romain Watteaux;Bruno Régaldo-Saint Blancard;François Rozet;Liam Holden Parker;Miles Cranmer;Shirley Ho,"Flatiron Institute;University of Colorado, Boulder;INRIA;Flatiron Institute;Flatiron Institute;University of Cambridge;Flatiron Institute;Rutgers University;University of Cambridge;Simons Foundation;Flatiron Institute;Flatiron Institute;Simons Foundation;University of Cambridge;Flatiron Institute/Simons Foundation;Los Alamos National Laboratory;University of California, Berkeley;University of Cambridge;Princeton University;CEA;Flatiron Institute;Flatiron Institute;Flatiron Institute;University of Cambridge;Carnegie Mellon University;The University of Tokyo",Postdoc;PhD student;PhD student;Postdoc;Postdoc;Postdoc;Full Professor;Assistant Professor;Director of the GK Batchelor Laboratory;Postdoc;Researcher;Postdoc;Researcher;Full Professor;Postdoc;Researcher;Postdoc;PhD student;PhD student;Researcher;Postdoc;Intern;Researcher;Assistant Professor;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/97882,,,,
6,1,-0.08406016,0.2851326,2,-0.1175666686646391,0.3253834673790484,"[0.005008124925562198, 5.5044140938591485e-17, 0.9917447580233327, 6.478328695429739e-16, 0.0032471170511043233]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,00uVk06eVK,On the Noise Robustness of In-Context Learning for Text Generation,In-Context Learning;Large Language Models;Noise Robustness,6.333333333333333,3.0,Hongfu Gao;Feipeng Zhang;Wenyu Jiang;Jun Shu;Feng Zheng;Hongxin Wei,Xi'an Jiaotong University;Xi'an Jiaotong University;Nanjing University;Xi'an Jiaotong University;Southern University of Science and Technology;Southern University of Science and Technology,MS student;Full Professor;PhD student;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96962,,,https://openreview.net/forum?id=00uVk06eVK,/media/PosterPDFs/NeurIPS%202024/96962.png?t=1731587881.4159098
6,2,-0.16364236,-0.11411294,4,-0.213519426706877,-0.006297675711616576,"[0.2897856112268587, 8.896128783402113e-08, 1.006857662816514e-11, 0.019300439558233445, 0.6909138602435515]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,01I55gys19,Few-Class Arena: A Benchmark for Efficient Vision Model Selection and Dataset Difficulty,few-class;efficiency;neural network;convolutional neural network;transformer;dataset difficulty measurement;scaling law,5.0,3.3333333333333335,Bryan Bo Cao;Lawrence O'Gorman;Michael Coss;Shubham Jain,Nokia networks GmbH;State University of New York at Stony Brook,Intern;Assistant Professor,,,,,
6,3,0.07371062,-0.27021888,3,-0.1265023537202139,-0.2905588727955389,"[0.2235818836065564, 0.10354814000419385, 5.039058625248685e-24, 0.6728694092500703, 5.671391793058145e-07]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,01XV5Za56k,Testing Calibration in Nearly-Linear Time,Calibration;Property testing;Linear programming,6.25,3.25,Lunjia Hu;Arun Jambulapati;Kevin Tian;Chutong Yang,Stanford University;Stanford University;Stanford University;University of Texas at Austin,PhD student;PhD student;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96961,,,https://openreview.net/forum?id=01XV5Za56k,
6,4,-0.1284643,0.3103237,2,-0.1175666686646391,0.3253834673790484,"[0.0005367880254623169, 7.767036690518774e-20, 0.9981559184229105, 2.4292512588082065e-18, 0.0013072935516272623]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,01lhHg8H9p,GLBench: A Comprehensive Benchmark for Graph with Large Language Models,Graph learning;Large Language Model;Zero-Shot,6.75,4.0,Yuhan Li;Peisong Wang;Xiao Zhu;Aochuan Chen;Haiyun Jiang;Deng Cai;Victor Wai Kin Chan;Jia Li,"Hong Kong University of Science and Technology;Tsinghua University;Beijing University of Posts and Telecommunications;Hong Kong University of Science and Technology;Tencent AI Lab;Tencent AI Lab;Shenzhen International Graduate School, Tsinghua University;Hong Kong University of Science and Technology",PhD student;MS student;Undergrad student;PhD student;Researcher;Research Scientist;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97881,,,,/media/PosterPDFs/NeurIPS%202024/97881.png?t=1731478194.2539835
6,5,-0.23808402,0.26056772,2,-0.1175666686646391,0.3253834673790484,"[0.00011126554996275983, 9.517609409306858e-22, 0.9852991951326828, 1.5111515645514626e-17, 0.01458953931735452]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,01qa1ZJs65,Bridge the Modality and Capability Gaps in Vision-Language Model Selection,Vision-Language Model;Model Selection;Zero-Shot Image Classification,5.25,4.0,Chao Yi;Yuhang He;De-Chuan Zhan;Han-Jia Ye,Nanjing University;Nanjing University;Nanjing University;Nanjing University,MS student;Undergrad student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96960,,,https://openreview.net/forum?id=01qa1ZJs65,/media/PosterPDFs/NeurIPS%202024/96960.png?t=1731123927.9174762
6,6,-0.10493148,-0.30384988,3,-0.1265023537202139,-0.2905588727955389,"[0.17908185188499892, 0.00016383056716156604, 2.0321803435926737e-24, 0.8204915009807375, 0.0002628165671020443]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,01s5ODIHKd,FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space,deep watermarking;latent frequency optimization,5.5,3.75,YiYang Guo;Ruizhe Li;Mude Hui;Hanzhong Allan Guo;Chen Zhang;Chuangjian Cai;Le Wan;Shangfei Wang,"University of Science and Technology of China;University of California, Santa Cruz;Renmin University of China;Tsinghua University;University of Science and Technology of China;University of Science and Technology of China",MS student;PhD student;MS student;PhD student;Full Professor;PhD student,https://neurips.cc/virtual/2024/poster/96959,,,https://openreview.net/forum?id=01s5ODIHKd,/media/PosterPDFs/NeurIPS%202024/96959.png?t=1730176108.8718698
6,7,-0.295713,-0.42771262,3,-0.1265023537202139,-0.2905588727955389,"[0.09666194646076866, 5.379658882231334e-07, 2.5214009629116803e-32, 0.9032910742185667, 4.6441354776495485e-05]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,02CIZ8qeDc,PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection,3D anomaly detection;Zero-shot 3D anomaly detection,6.0,3.6666666666666665,Qihang Zhou;Jiangtao Yan;Shibo He;Wenchao Meng;Jiming Chen,Zhejiang University;Zhejiang University;Zhejiang University;Zhejiang University,PhD student;MS student;Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96958,,,https://openreview.net/forum?id=02CIZ8qeDc,/media/PosterPDFs/NeurIPS%202024/96958.png?t=1731476864.9817398
6,8,-0.3188932,-0.023905918,4,-0.213519426706877,-0.006297675711616576,"[0.0030557911924382086, 1.0065564922140413e-14, 1.9276543666892798e-07, 1.278791111462853e-06, 0.9969427372510036]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,02HWT9c4Lp,Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion,Semantic Scene completion，Voxel Proposal，Knowledge Distillation,5.5,4.0,Lubo Wang;Di Lin;Kairui Yang;Ruonan Liu;Qing Guo;Wuyuan Xie;Miaohui Wang;Lingyu Liang;Yi Wang;Ping Li,"Tianjin University;Tianjin University;Tianjin University;Tianjin University; Agency for Science, Technology and Research (A*STAR));Department of Software Engineering, Shenzhen University;Shenzhen University;South China University of Technology;Shenzhen University;The Hong Kong Polytechnic University",MS student;Associate Professor;PhD student;Associate Professor;Researcher;Associate Professor;Associate Professor;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96957,,,https://openreview.net/forum?id=02HWT9c4Lp,/media/PosterPDFs/NeurIPS%202024/96957.png?t=1731159292.6143699
6,9,0.52375084,0.03593809,1,0.40562164791490474,-0.08153763996448539,"[5.321675473541919e-05, 0.999945315418464, 7.044303441950591e-18, 1.4678268006942402e-06, 3.826541626169934e-23]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,02r24A8doi,Achieving Constant Regret in Linear Markov Decision Processes,Reinforcement learning;Constant regret;Misspecified linear MDP,5.25,2.75,Weitong Zhang;Zhiyuan Fan;Jiafan He;Quanquan Gu,"Massachusetts Institute of Technology;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles",PhD student;PhD student;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96956,,,https://openreview.net/forum?id=02r24A8doi,
6,10,-0.24769914,0.06194072,4,-0.213519426706877,-0.006297675711616576,"[0.004187949880500522, 5.889071236584682e-15, 0.0001412609762489838, 1.2291106556193779e-08, 0.995670776852138]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,04EC4ZnZJj,MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers,transformer architecture;large language model;computational complexity reduction,6.0,3.5,Ning Ding;Yehui Tang;Haochen Qin;Zhenli Zhou;Chao Xu;Lin Li;Kai Han;Liao Heng;Yunhe Wang,"Peking University;Huawei Technologies Ltd.;Huawei Technologies Ltd.;Peking University;Peking University;Huawei Noah's Ark Lab;, Tsinghua University;Huawei Noah's Ark Lab",PhD student;Researcher;Researcher;MS student;Full Professor;Principal Researcher;Principal Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96955,,,https://openreview.net/forum?id=04EC4ZnZJj,
6,11,0.45866024,0.07679337,1,0.40562164791490474,-0.08153763996448539,"[0.0030354650128167878, 0.9969584165658768, 9.581152639758818e-14, 6.118421210544797e-06, 1.260095084444745e-18]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,06JRFVK88O,Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games,Multi-agent Reinforcement Learning;Imitation Learning,6.666666666666667,3.0,The Viet Bui;Tien Anh Mai;Thanh Hong Nguyen,Singapore Management University;University of Oregon;Singapore Management University,Assistant Professor;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96954,,,https://openreview.net/forum?id=06JRFVK88O,/media/PosterPDFs/NeurIPS%202024/96954.png?t=1731744891.8886228
6,12,-0.21952832,-0.2596673,3,-0.1265023537202139,-0.2905588727955389,"[0.21841069663409224, 6.686199479308923e-07, 4.9407959278630574e-20, 0.745849823099772, 0.03573881164618782]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,06Vt6f2js7,SyncTweedies: A General Generative Framework Based on Synchronized Diffusions,Diffusion Models;Synchronization;Texturing;3D Gaussian Splatting;Mesh;Panorama,6.666666666666667,3.6666666666666665,Jaihoon Kim;Juil Koo;Kyeongmin Yeo;Minhyuk Sung,KAIST;Adobe Systems;Korea Advanced Institute of Science & Technology;Korea Advanced Institute of Science & Technology,MS student;Intern;Undergrad student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96953,,,https://openreview.net/forum?id=06Vt6f2js7,
6,13,0.5387558,-0.021885695,1,0.40562164791490474,-0.08153763996448539,"[6.306293422262025e-06, 0.999992057141744, 2.852781103619996e-21, 1.6365648337119212e-06, 7.71620248008606e-25]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,07N0qoaZ2L,Improved Analysis for Bandit Learning in Matching Markets,Bandits;Matching markets;Stable matching;Stable regret;Exploration and exploitation;$\alpha$-condition,5.5,3.0,Fang Kong;Zilong Wang;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;John Hopcroft Center, Shanghai Jiao Tong University",PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96952,,,https://openreview.net/forum?id=07N0qoaZ2L,/media/PosterPDFs/NeurIPS%202024/96952.png?t=1731746661.9360106
6,14,-0.31746334,-0.03755091,4,-0.213519426706877,-0.006297675711616576,"[0.0038507270314282744, 2.678886939491955e-14, 5.4508839357120254e-08, 3.527337561874647e-06, 0.9961456911221436]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,08A6X7FSTs,Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text,Text-to-3D Scene Generation;Latent Diffusion Models,5.5,4.5,Xinyang Li;Zhangyu Lai;Linning Xu;Yansong Qu;Liujuan Cao;Shengchuan Zhang;Bo Dai;Rongrong Ji,Xiamen University;Xiamen University;Xiamen University;Xiamen University;Xiamen University;Shanghai AI Laboratory;Xiamen University;The Chinese University of Hong Kong,PhD student;MS student;PhD student;Full Professor;Assistant Professor;Scientist;Full Professor;Ph.D. student,https://neurips.cc/virtual/2024/poster/96951,,,https://openreview.net/forum?id=08A6X7FSTs,/media/PosterPDFs/NeurIPS%202024/96951.png?t=1732593534.8700738
6,15,0.21572201,0.15297481,0,0.043912488447873634,0.0009302794543285151,"[0.9997859722859438, 0.0001926524614287751, 2.0302554860096457e-05, 9.221159467788878e-07, 1.5058182043427845e-07]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,08GbdALmEs,Learning Versatile Skills with Curriculum Masking,reinforcement learning;unsupervised pretraining;masked prediction;curriculum learning,5.25,3.25,Yao Tang;Zhihui Xie;Zichuan Lin;Deheng Ye;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;Tencent AI Lab;Tencent;John Hopcroft Center, Shanghai Jiao Tong University",Undergrad student;MS student;Researcher;Principal Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96950,,,https://openreview.net/forum?id=08GbdALmEs,/media/PosterPDFs/NeurIPS%202024/96950.png?t=1733319308.3295946
6,16,-0.17784788,-0.16018736,4,-0.213519426706877,-0.006297675711616576,"[0.39746872941152744, 3.396638828718147e-07, 5.438727670807446e-14, 0.1270095896924722, 0.4755213412320632]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,08nbMTxazb,Chicks4FreeID: A Benchmark Dataset for Chicken Re-Identification,animal re-identification;chicken re-identification;chicken dataset;re-identification dataset;benchmark dataset;closed-set re-identification;computer vision;chicken instance segmentation;poultry;livestock,4.75,4.0,Daria Kern;Tobias Schiele;Ulrich Klauck;Winfred Ingabire,Glasgow Caledonian University;Hochschule Aalen;Glasgow Caledonian University,PhD student;Full Professor;Lecturer,,,,,
6,17,0.12485067,-0.17534988,0,0.043912488447873634,0.0009302794543285151,"[0.406936556964098, 0.1930597955657958, 1.8827603809941503e-18, 0.4000027045139927, 9.429561134520774e-07]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,08oUnmtj8Q,FSEO: A Few-Shot Evolutionary Optimization Framework for Expensive Multi-Objective Optimization and Constrained Optimization,Expensive optimization;few-shot optimization;multi-objective optimization;constrained optimization;surrogate-assisted evolutionary optimization,4.5,3.5,Xunzhao Yu,,,,,,,
6,18,-0.045080878,-0.32160506,3,-0.1265023537202139,-0.2905588727955389,"[0.19086188289850325, 0.0024212684469381604, 2.5257675727429717e-26, 0.8067001870311313, 1.666162342745233e-05]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,09RKw0vXjR,Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations,feature selection;sparse coding;dictionary learning;compressed sensing;iterative hard thresholding;pruning method,5.75,3.0,Yasutoshi Ida;Sekitoshi Kanai;Atsutoshi Kumagai;Tomoharu Iwata;Yasuhiro Fujiwara,NTT;NTT;NTT;NTT;NTT,Researcher;Researcher;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96949,,,https://openreview.net/forum?id=09RKw0vXjR,/media/PosterPDFs/NeurIPS%202024/96949.png?t=1733375377.8112724
6,19,-0.29219365,-0.1354431,4,-0.213519426706877,-0.006297675711616576,"[0.038959298753717155, 7.170950767177417e-11, 2.577775877108544e-12, 0.004055844775303118, 0.9569848563966926]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,09nyBqSdUz,RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance,Consistent image generation;Diverse image generation;Improve temporal-consistency;Feature injection from multiple images,5.5,4.0,Jiaojiao Fan;Haotian Xue;Qinsheng Zhang;Yongxin Chen,Georgia Institute of Technology;Georgia Institute of Technology;Georgia Institute of Technology;NVIDIA,PhD student;PhD student;Associate Professor;Research Intern,https://neurips.cc/virtual/2024/poster/96948,,,https://openreview.net/forum?id=09nyBqSdUz,/media/PosterPDFs/NeurIPS%202024/96948.png?t=1731392354.7708242
6,20,0.22983314,0.005944166,0,0.043912488447873634,0.0009302794543285151,"[0.8449321285960073, 0.15071242228121381, 1.3326342628702765e-10, 0.004355407783621255, 4.120589399976975e-08]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0AumdfLzpK,A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations,Visual Reinforcement Learning;Generalization,6.0,4.0,Wonil Song;Hyesong Choi;Kwanghoon Sohn;Dongbo Min,Yonsei Univ.;Ewha Womans University;Yonsei University;Ewha Womans University,PhD student;PhD student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96947,,,https://openreview.net/forum?id=0AumdfLzpK,/media/PosterPDFs/NeurIPS%202024/96947.png?t=1732451612.1247888
6,21,-0.2313607,0.15489271,4,-0.213519426706877,-0.006297675711616576,"[0.004251121150269082, 6.156926601060302e-17, 0.10227756242466825, 1.157997327147968e-11, 0.8934713164134828]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0AwMciNShl,"Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality",Human evaluation;text-to-video models,5.25,4.0,Tianle Zhang;Langtian Ma;Yuchen Yan;Yuchen Zhang;Yue Yang;Ziyao Guo;Wenqi Shao;Kai Wang;Yang You;Yu Qiao;Ping Luo;Kaipeng Zhang,University of Electronic Science and Technology of China;Southern University of Science and Technology;The University of Nottingham Ningbo China;University of Electronic Science and Technology of China;Xidian University;Shanghai AI Laboratory;National University of Singapore;National University of Singapore;Shanghai AI Laboratory;The University of Hong Kong;Shanghai Jiaotong University,Undergrad student;Undergrad student;Undergrad student;Undergrad student;MS student;Researcher;PhD student;Professor;Researcher;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96946,,,https://openreview.net/forum?id=0AwMciNShl,/media/PosterPDFs/NeurIPS%202024/96946.png?t=1729079669.652648
6,22,0.44196302,-0.22339565,1,0.40562164791490474,-0.08153763996448539,"[7.225441277065115e-06, 0.9999647043408666, 3.646063646962987e-30, 2.8070217856084183e-05, 3.607156717169682e-22]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0C3bLHwjsY,Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions,Online Matching;Competitive Analysis;Fairness Maximization,6.25,3.0,Will Ma;Pan Xu,Columbia University;New Jersey Institute of Technology,Assistant Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96945,,,https://openreview.net/forum?id=0C3bLHwjsY,/media/PosterPDFs/NeurIPS%202024/96945.png?t=1731641014.5806563
6,23,0.31953293,-0.23248373,1,0.40562164791490474,-0.08153763996448539,"[0.00046713113825582944, 0.99812252285458, 2.679346807474022e-27, 0.00141034600716352, 5.006821233642257e-16]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0DE1dLMW2b,Quantum algorithm for large-scale market equilibrium computation,market equilibrium computation;quantum algorithm,6.0,2.75,Po-Wei Huang;Patrick Rebentrost,Centre for Quantum Technologies;National University of Singapore,Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96944,,,https://openreview.net/forum?id=0DE1dLMW2b,/media/PosterPDFs/NeurIPS%202024/96944.png?t=1731426989.5298698
6,24,0.0025802255,-0.08199731,0,0.043912488447873634,0.0009302794543285151,"[0.9527579241468094, 0.00016298945000105242, 1.5310443025257466e-11, 0.03854830453733663, 0.00853078185054256]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0EfUYVMrLv,Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment,non-stationary environments;continuous distribution shift;test-time adaptation;unlabeled data,6.666666666666667,4.0,Zhen-Yu Zhang;Zhiyu Xie;Huaxiu Yao;Masashi Sugiyama,"RIKEN;Stanford University;Department of Computer Science, University of North Carolina at Chapel Hill;The University of Tokyo",Postdoc;MS student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96943,,,https://openreview.net/forum?id=0EfUYVMrLv,/media/PosterPDFs/NeurIPS%202024/96943.png?t=1731687693.6296034
6,25,0.023439856,-0.079839304,0,0.043912488447873634,0.0009302794543285151,"[0.9564430183215142, 0.0003828275205803681, 1.0817814105920674e-11, 0.03984697411652047, 0.003327180030567076]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0G0VpMjKyV,Sketching for Distributed Deep Learning: A Sharper Analysis,sketching;distributed learning;federated learning;optimization,5.666666666666667,4.0,Mayank Shrivastava;Berivan Isik;Qiaobo Li;Sanmi Koyejo;Arindam Banerjee,"University of Illinois, Urbana Champaign;Stanford University;Department of Computer Science, University of Illinois at Urbana-Champaign;University of Illinois, Urbana Champaign;Google",MS student;PhD student;PhD student;Professor;Research Scientist,https://neurips.cc/virtual/2024/poster/96942,,,https://openreview.net/forum?id=0G0VpMjKyV,/media/PosterPDFs/NeurIPS%202024/96942.png?t=1733481266.9121125
6,26,-0.06371302,0.3954228,2,-0.1175666686646391,0.3253834673790484,"[0.0007338652253084635, 8.645194370719398e-21, 0.9992414795554291, 8.007826129412912e-22, 2.4655219262536967e-05]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,0G5OK5vmmg,WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts,Benchmark;Large Language Models;Classical Chinese Literature and Language Arts,6.25,2.75,Jiahuan Cao;Yang Liu;Yongxin Shi;Kai Ding;Lianwen Jin,South China University of Technology;South China University of Technology;South China University of Technology;INTSIG Information;South China University of Technology,MS student;MS student;PhD student;Researcher;Professor,https://neurips.cc/virtual/2024/poster/97880,,,,/media/PosterPDFs/NeurIPS%202024/97880.png?t=1730896668.2191207
6,27,-0.2963673,0.015343715,4,-0.213519426706877,-0.006297675711616576,"[0.002549592953706817, 3.5286589772117295e-15, 4.643328641146002e-06, 1.1343958700545684e-07, 0.9974456502780614]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0G8AXwtmy2,T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition,harmful dataset;harmful content detection;Vision Language Model,6.5,3.75,Chen Yeh;You-Ming Chang;Wei-Chen Chiu;Ning Yu,National Yang Ming Chiao Tung University;National Yang Ming Chiao Tung University;National Chiao Tung University,MS student;MS student;Associate Professor,https://neurips.cc/virtual/2024/poster/97879,,,,/media/PosterPDFs/NeurIPS%202024/97879.png?t=1730218737.4487233
6,28,0.08612508,0.3898904,2,-0.1175666686646391,0.3253834673790484,"[0.10987600820809872, 1.352102133070943e-14, 0.8901220459960933, 4.768879524368891e-18, 1.945795794442883e-06]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,0Gl5WxY6es,Grounding Multimodal Large Language Models in Actions,Embodied AI;Multimodal Large Language Models;Reinforcement Learning;Imitation Learning,6.0,3.6666666666666665,Andrew Szot;Bogdan Mazoure;Harsh Agrawal;R Devon Hjelm;Zsolt Kira;Alexander T Toshev,Georgia Institute of Technology;Apple;Apple;Apple;Georgia Institute of Technology;Apple,PhD student;Research Scientist;Researcher;Researcher;Assistant Professor;research scientist,https://neurips.cc/virtual/2024/poster/96941,,,https://openreview.net/forum?id=0Gl5WxY6es,
6,29,-0.20296153,0.2345368,2,-0.1175666686646391,0.3253834673790484,"[0.0009835202400023044, 3.901293247739843e-19, 0.9329258935926166, 2.9441276276428024e-15, 0.06609058616737815]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,0Gmi8TkUC7,GenAI Arena: An Open Evaluation Platform for Generative Models,Evaluation;Benchmark;Platform;Generative Model,6.0,3.5,Dongfu Jiang;Max Ku;Tianle Li;Yuansheng Ni;Shizhuo Sun;Rongqi Fan;Wenhu Chen,Allen Institute for Artificial Intelligence;University of Waterloo;University of Waterloo;University of Toronto;NVIDIA;University of Waterloo,Intern;MS student;MS student;Undergrad student;Intern;Assistant Professor,https://neurips.cc/virtual/2024/poster/97878,,,,/media/PosterPDFs/NeurIPS%202024/97878.png?t=1730329031.3167162
6,30,-0.3021013,-0.23802479,3,-0.1265023537202139,-0.2905588727955389,"[0.20442085110541172, 9.557603307081789e-09, 9.546982346115412e-18, 0.5005507276365592, 0.2950284117004257]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,0HRRNEAQFp,A General Protocol to Probe Large Vision Models for 3D Physical Understanding,3D physical scene understanding; Representation probing protocol; Benchmark and evaluation,6.333333333333333,4.0,Guanqi Zhan;Chuanxia Zheng;Weidi Xie;Andrew Zisserman,University of Oxford;University of Oxford;Shanghai Jiaotong University,PhD student;Postdoc;Associate Professor,https://neurips.cc/virtual/2024/poster/96940,,,https://openreview.net/forum?id=0HRRNEAQFp,/media/PosterPDFs/NeurIPS%202024/96940.png?t=1731705235.0575316
6,31,0.40233114,0.06031101,1,0.40562164791490474,-0.08153763996448539,"[0.01942977447261041, 0.98052498308923, 1.1752669246179334e-12, 4.524243698294105e-05, 1.3796879615757304e-15]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0JSKjdePGq,When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL,reinforcement learning;continuous-time,6.75,3.25,Lenart Treven;Bhavya Sukhija;Yarden As;Florian Dorfler;Andreas Krause,"Swiss Federal Institute of Technology;ETHZ - ETH Zurich;Department of Computer Science, ETHZ - ETH Zurich;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96939,,,https://openreview.net/forum?id=0JSKjdePGq,/media/PosterPDFs/NeurIPS%202024/96939.png?t=1730197260.75527
6,32,-0.31179968,-0.050893012,4,-0.213519426706877,-0.006297675711616576,"[0.005198036775389479, 9.136520663328963e-14, 1.469752049110916e-08, 1.0146977357875145e-05, 0.9947918015496406]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0KseSacluJ,CoFie: Learning Compact Neural Surface Representations with Coordinate Fields,Neural Surface Representation;Shape Auto-Decoding;Coordinate Field.,5.0,4.0,Hanwen Jiang;Haitao Yang;Georgios Pavlakos;Qixing Huang,University of Texas at Austin;The University of Texas at Austin;University of Texas at Austin;University of Texas at Austin,PhD student;PhD student;Assistant Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96938,,,https://openreview.net/forum?id=0KseSacluJ,
6,33,0.11298243,0.035079706,0,0.043912488447873634,0.0009302794543285151,"[0.9991932383207575, 0.00028715153745417267, 8.37547451009563e-08, 0.000411931802488253, 0.00010759458455488834]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0KvYLaTBTE,Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference,Generative models;Reinforcement learning;Decision transformer,6.333333333333333,3.0,Deqian Kong;Dehong Xu;Minglu Zhao;Bo Pang;Jianwen Xie;Andrew Lizarraga;Yuhao Huang;Sirui Xie;Ying Nian Wu,"University of California, Los Angeles;Amazon;University of California, Los Angeles;University of California, Los Angeles;Xi'an Jiaotong University;University of California, Los Angeles;University of California, Los Angeles;UCLA",PhD student;Intern;PhD student;PhD student;PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96937,,,https://openreview.net/forum?id=0KvYLaTBTE,
6,34,-0.23456638,0.06657637,4,-0.213519426706877,-0.006297675711616576,"[0.005440968882615237, 1.1776771052346639e-14, 0.0001889231676928584, 1.2981835333939367e-08, 0.9943700949678448]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0LXotew9Du,KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization,Quantization;KV Cache;LLM Inference;Compression;Long Context Length,6.25,3.25,Coleman Richard Charles Hooper;Sehoon Kim;Hiva Mohammadzadeh;Michael W. Mahoney;Sophia Shao;Kurt Keutzer;Amir Gholami,"University of California, Berkeley;University of California, Berkeley;University of California, Berkeley;University of California, Berkeley",PhD student;PhD student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96936,,,https://openreview.net/forum?id=0LXotew9Du,
6,35,0.11017645,-0.16371755,0,0.043912488447873634,0.0009302794543285151,"[0.5158824133942722, 0.10189202385446351, 1.690689060429677e-17, 0.38222193114352276, 3.631607741480958e-06]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0Lb8vZT1DB,Reliable Learning of Halfspaces under Gaussian Marginals,reliable learning;agnostic learning;halfspace;proper leaning;statistical query,7.25,2.25,Ilias Diakonikolas;Lisheng Ren;Nikos Zarifis,"University of Wisconsin - Madison;University of Wisconsin - Madison;University of Wisconsin, Madison",Full Professor;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96935,,,https://openreview.net/forum?id=0Lb8vZT1DB,
6,36,0.1429859,0.059452157,0,0.043912488447873634,0.0009302794543285151,"[0.9994183305234318, 0.00041772035268836875, 2.6136369615193777e-07, 0.0001438061733162682, 1.9881586867426388e-05]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0LfgE6kvKZ,Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning,Federated Learning; Model Merging,5.0,3.6666666666666665,Minghui Chen;Meirui Jiang;Xin Zhang;Qi Dou;Zehua Wang;Xiaoxiao Li,"University of British Columbia;Meta Facebook;The Chinese University of Hong Kong;University of British Columbia;University of British Columbia;Department of Computer Science and Engineering, The Chinese University of Hong Kong",PhD student;Research Scientist;Assistant Professor;Researcher;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96934,,,https://openreview.net/forum?id=0LfgE6kvKZ,/media/PosterPDFs/NeurIPS%202024/96934.png?t=1731518093.5294044
6,37,-0.040502112,0.02318828,0,0.043912488447873634,0.0009302794543285151,"[0.8134462427420744, 2.68998901880226e-07, 2.3579164791781633e-06, 0.00016428372417064512, 0.18638684661837399]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0Lr9HQijA1,Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations,Imprecise Label Learning,5.75,3.0,Hao Chen;Ankit Shah;Jindong Wang;Ran Tao;Yidong Wang;Xiang Li;Xing Xie;Masashi Sugiyama;Rita Singh;Bhiksha Raj,"Carnegie Mellon University;Accenture;Microsoft Research;Peking University;Microsoft Research Asia;The University of Tokyo;School of Computer Science, Carnegie Mellon University;Mohamed bin Zayed University of Artificial Intelligence",PhD student;Principal Researcher;Researcher;PhD student;Senior Principal Researcher;Full Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96933,,,https://openreview.net/forum?id=0Lr9HQijA1,/media/PosterPDFs/NeurIPS%202024/96933.png?t=1731704880.9846606
6,38,-0.06471333,0.08954511,0,0.043912488447873634,0.0009302794543285151,"[0.5245218844402633, 2.0856671768436535e-09, 0.0008719931651293007, 1.3272806592068497e-06, 0.474604793028281]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0MXzbAv8xy,GFT: Graph Foundation Model with Transferable Tree Vocabulary,Graph Foundation Model;Transferability;Computation Tree;Graph Neural Network,6.0,3.75,Zehong Wang;Zheyuan Zhang;Nitesh V Chawla;Chuxu Zhang;Yanfang Ye,University of Notre Dame;University of Notre Dame;University of Notre Dame;University of Notre Dame,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96932,,,https://openreview.net/forum?id=0MXzbAv8xy,
6,39,0.06407858,0.09707585,0,0.043912488447873634,0.0009302794543285151,"[0.9978691066319375, 1.690401535315965e-06, 5.864181325370837e-05, 6.1406211405519616e-06, 0.002064420532133252]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0NMzBwqaAJ,Not All Tokens Are What You Need for Pretraining,pre-training;next token prediction;data optimization;data selection,7.666666666666667,4.0,Zhenghao Lin;Zhibin Gou;Yeyun Gong;Xiao Liu;yelong shen;Ruochen Xu;Chen Lin;Yujiu Yang;Jian Jiao;Nan Duan;Weizhu Chen,Xiamen University;Microsoft;Microsoft Research Asia;Microsoft Research;Xiamen University;Tsinghua University;Microsoft;Microsoft Research Asia;Microsoft GenAI,MS student;Intern;Researcher;Researcher;Full Professor;Full Professor;Principal Researcher;Principal Researcher;Vice President,https://neurips.cc/virtual/2024/poster/96931,,,https://openreview.net/forum?id=0NMzBwqaAJ,/media/PosterPDFs/NeurIPS%202024/96931.png?t=1733724962.7310221
6,40,-0.021407472,0.09407413,0,0.043912488447873634,0.0009302794543285151,"[0.8747557894270023, 2.4529083299372656e-08, 0.0005622886231478457, 2.5725324534389878e-06, 0.12467932488831292]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0NQzQVu9tY,DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors,representation learning;offline reinforcement learning;behavioral cloning;visual distractor,7.0,3.0,Joseph Ortiz;Antoine Dedieu;Wolfgang Lehrach;J Swaroop Guntupalli;Carter Wendelken;Ahmad Humayun;Sivaramakrishnan Swaminathan;Guangyao Zhou;Miguel Lazaro-Gredilla;Kevin Patrick Murphy,Google DeepMind;Google DeepMind;Google Deepmind;Google DeepMind;Google;Google DeepMind;Google DeepMind;Google DeepMind;Google Deepmind;Google,Researcher;Researcher;Researcher;Researcher;Researcher;Researcher;Research Engineer;Research Scientist;Research Scientist;Principal Researcher,https://neurips.cc/virtual/2024/poster/97877,,,,/media/PosterPDFs/NeurIPS%202024/97877.png?t=1733266397.4133346
6,41,-0.056248758,0.025906589,0,0.043912488447873634,0.0009302794543285151,"[0.688519730291717, 9.373205243520972e-08, 4.0586515821800205e-06, 0.00010420867454162991, 0.31137190865010667]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0SMhqvgHST,EEVEE and GATE: Finding the right benchmarks and how to run them seamlessly,multi-modal;benchmarks;machine learning;model evaluation;benchmark frameworks,6.0,4.0,Antreas Antoniou;Eleni Triantafillou;Hugo Larochelle;Sebastien Montella;Fady Rezk;Kiyoon Kim;Linus Ericsson;Pavlos Vougiouklis;Justin Engelmann;Elliot J. Crowley;Srihari Humbarwadi;Yi Liu;Guang Yang;Jeff Z. Pan;Amos Storkey,"Google;Google;Huawei Technologies Ltd.;Samsung;Deargen;University of Edinburgh, University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh, University of Edinburgh;University of Edinburgh",Researcher;Research Scientist;Researcher;Intern;Researcher;Postdoc;Researcher;Assistant Professor;Researcher;Full Professor;Full Professor,,,,,
6,42,-0.15132618,0.02146309,4,-0.213519426706877,-0.006297675711616576,"[0.06941086446236253, 1.0875020795062324e-10, 4.156195530159285e-06, 6.275188776566903e-06, 0.9305787040445804]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0SRJBtTNhX,IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors,Graph Machine Learning;Graph Data Augmentation;Graph Neural Networks,5.5,4.0,Shenghe Zheng;Hongzhi Wang;Xianglong Liu,Harbin Institute of Technology;Harbin Institute of Technology;Harbin Institute of Technology,MS student;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96930,,,https://openreview.net/forum?id=0SRJBtTNhX,/media/PosterPDFs/NeurIPS%202024/96930.png?t=1732617637.3891017
6,43,-0.18518934,0.0027779788,4,-0.213519426706877,-0.006297675711616576,"[0.03248035801159781, 2.339698742154821e-11, 8.375307457803654e-07, 6.857423308069297e-06, 0.9675119470109514]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0T8xRFrScB,Benchmarking Counterfactual Image Generation,benchmark;causal inference;counterfactual image generation,7.25,3.75,Thomas Melistas;Nikos Spyrou;Nefeli Gkouti;Pedro Sanchez;Athanasios Vlontzos;Yannis Panagakis;Giorgos Papanastasiou;Sotirios A. Tsaftaris,"University of Athens;University of Athens;University of Athens;University of Edinburgh, University of Edinburgh;Spotify;Pfizer;University of Edinburgh",PhD student;PhD student;PhD student;PhD student;Researcher;Principal Researcher;Professor in machine learning and computer vision,https://neurips.cc/virtual/2024/poster/97876,,,,/media/PosterPDFs/NeurIPS%202024/97876.png?t=1731712408.6398222
6,44,0.5118622,-0.024860546,1,0.40562164791490474,-0.08153763996448539,"[1.6887971379096418e-05, 0.9999793701871638, 1.4308556803277303e-20, 3.7418414572255046e-06, 2.9902762555639835e-23]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0TUMAAb3of,Queueing Matching Bandits with Preference Feedback,Bandits;Queue;Preference Feedback,6.0,2.5,Jung-hun Kim;Min-hwan Oh,Seoul National University;Seoul National University,Assistant Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96929,,,https://openreview.net/forum?id=0TUMAAb3of,/media/PosterPDFs/NeurIPS%202024/96929.png?t=1733803835.532587
6,45,-0.0018669573,0.3644946,2,-0.1175666686646391,0.3253834673790484,"[0.008879172025833729, 4.12002450392968e-17, 0.9910869696161266, 1.1319358753536635e-18, 3.385835803963554e-05]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,0VeSCjRDBy,Adversarial Moment-Matching Distillation of Large Language Models,Knowledge distillation;Large language models;Imitation learning;Moment-matching;Adversarial training,6.25,3.0,Chen Jia,,,https://neurips.cc/virtual/2024/poster/96928,,,https://openreview.net/forum?id=0VeSCjRDBy,/media/PosterPDFs/NeurIPS%202024/96928.png?t=1731660620.7591212
6,46,-0.24925767,0.015651966,4,-0.213519426706877,-0.006297675711616576,"[0.006095240639989062, 9.255833041956373e-14, 3.193518351128659e-06, 3.733504651074061e-07, 0.9939011924911021]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0WCFI2Qx85,ScaleKD: Strong Vision Transformers Could Be Excellent Teachers,knowledge distillation;model compression;training acceleration;vision transformer;convolutional neural network;multi-layer perception,6.25,4.5,Jiawei Fan;Chao Li;Xiaolong Liu;Anbang Yao,Intel Labs China;Intel;Intel,Research Intern;Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96927,,,https://openreview.net/forum?id=0WCFI2Qx85,/media/PosterPDFs/NeurIPS%202024/96927.png?t=1731695837.2500114
6,47,0.2804453,-0.1894261,1,0.40562164791490474,-0.08153763996448539,"[0.003760135340085816, 0.9889412759457532, 2.7762626313952965e-23, 0.007298588713930806, 2.301525686124688e-13]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0XKvW4ijxp,Learning-Augmented Algorithms with Explicit Predictors,online algorithms;learning-augmented algorithms;scheduling;caching,6.0,4.0,Marek Elias;Haim Kaplan;Yishay Mansour;Shay Moran,"Bocconi University;Technion, Technion;School of Computer Science, Tel Aviv University",Assistant Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96926,,,https://openreview.net/forum?id=0XKvW4ijxp,/media/PosterPDFs/NeurIPS%202024/96926.png?t=1733319671.0065775
6,48,0.37225774,-0.11562894,1,0.40562164791490474,-0.08153763996448539,"[0.0004910161647660696, 0.9990913852722552, 2.3966283609794265e-21, 0.00041759856297881757, 9.880098219590401e-17]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0XeNkkENuI,The Road Less Scheduled,Stochastic Optimization;Optimization;Convex Optimization;Learning Rates;Learning Rate Schedules,7.5,3.5,Aaron Defazio;Xingyu Alice Yang;Ahmed Khaled;Konstantin Mishchenko;Harsh Mehta;Ashok Cutkosky,Meta;Meta;Princeton University;Samsung;Google Research;Boston University,Research Scientist;Research Engineer;PhD student;Researcher;Software Engineer;Assistant Professor,https://neurips.cc/virtual/2024/poster/96925,,,https://openreview.net/forum?id=0XeNkkENuI,/media/PosterPDFs/NeurIPS%202024/96925.png?t=1730837481.9895687
6,49,0.1460578,0.21914145,0,0.043912488447873634,0.0009302794543285151,"[0.992693549888278, 1.8181660855129116e-07, 0.0072970304761984, 2.149254959675366e-09, 9.235669660069014e-06]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0ZZMUjZJYF,Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study,LLMs;Learning by Teaching;Reasoning;Mathematical Reasoning;Code Synthesis;Weak-to-Strong Generalization;In-Context Learning;Prompting;Knowledge Distillation;Education-Inspired,6.5,4.0,Xuefei Ning;Zifu Wang;Shiyao Li;Zinan Lin;Peiran Yao;Tianyu Fu;Matthew B. Blaschko;Guohao Dai;Huazhong Yang;Yu Wang,Tsinghua University;KU Leuven;Tsinghua University;Microsoft;Infinigence;Shanghai Jiaotong University;Tsinghua University;Tsinghua University;KU Leuven,Research Assistant Professor;PhD student;PhD student;Senior Researcher;Researcher;Associate Professor;Full Professor;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96924,,,https://openreview.net/forum?id=0ZZMUjZJYF,/media/PosterPDFs/NeurIPS%202024/96924.png?t=1732367562.4969194
6,50,0.07159563,-0.024327766,0,0.043912488447873634,0.0009302794543285151,"[0.9933572961673326, 0.00045443045974787966, 1.0674730596939006e-09, 0.005537622311940988, 0.0006506499935056622]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0ZeONp33f0,Graph Neural Networks and Arithmetic Circuits,Machine Learning;Graph Neural Networks;Arithmetic Circuits;Computational Complexity,6.5,3.25,Timon Barlag;Vivian Holzapfel;Laura Strieker;Jonni Virtema;Heribert Vollmer,Universität Hannover;Leibniz Universität Hannover;Leibniz Universität Hannover;University of Sheffield;Leibniz Universität Hannover,PhD student;Undergrad student;PhD student;Lecturer;Full Professor,https://neurips.cc/virtual/2024/poster/96923,,,https://openreview.net/forum?id=0ZeONp33f0,/media/PosterPDFs/NeurIPS%202024/96923.png?t=1732106485.9402945
6,51,-0.078428976,-0.18954016,0,0.043912488447873634,0.0009302794543285151,"[0.532618075953391, 8.611525739241172e-05, 9.81802825946988e-17, 0.45476460745938685, 0.012531201329829688]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0aN7VWwp4g,Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting,Precipitation Nowcasting;Video Prediction;Fourier Analysis;Loss Function,6.0,4.0,Chiu-Wai Yan;Shi Quan Foo;Van-Hoan Trinh;Dit-Yan Yeung;Ka-Hing Wong;Wai-Kin Wong,Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology,Chair Professor;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96922,,,https://openreview.net/forum?id=0aN7VWwp4g,/media/PosterPDFs/NeurIPS%202024/96922.png?t=1731480203.951872
6,52,-0.23586994,0.37846398,2,-0.1175666686646391,0.3253834673790484,"[3.6193784012275168e-06, 4.4860143655524465e-27, 0.9999263063555642, 1.0457237243449384e-24, 7.007426603448809e-05]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,0bFXbEMz8e,FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions,generative models;material generation;chemistry;flow matching;large language models,6.0,4.333333333333333,Anuroop Sriram;Benjamin Kurt Miller;Ricky T. Q. Chen;Brandon M Wood,"Meta Facebook;University of Amsterdam;FAIR at Meta;FAIR Labs, Meta AI",Principal Researcher;PhD student;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96921,,,https://openreview.net/forum?id=0bFXbEMz8e,/media/PosterPDFs/NeurIPS%202024/96921.png?t=1730973273.143089
6,53,-0.15925287,-0.015642455,4,-0.213519426706877,-0.006297675711616576,"[0.08127721893417182, 4.983576217488065e-10, 1.6199536354462197e-07, 5.7784761006859086e-05, 0.9186648338111002]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0bINeW40u4,Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning,Medical Multi-modal Alignment;Eye-gaze;Radiology,6.25,3.5,Chong Ma;Hanqi Jiang;Wenting Chen;Yiwei Li;Zihao Wu;Xiaowei Yu;Zhengliang Liu;Lei Guo;Dajiang Zhu;Tuo Zhang;Dinggang Shen;Tianming Liu;Xiang Li,"Northwest Polytechnical University Xi'an;Beijing Jiaotong University;City University of Hong Kong;University of Georgia;University of Georgia;University of Texas at Arlington, University of Texas at Arlington;University of Georgia;University of Texas at Arlington;Northwestern Polytechnical University;ShanghaiTech University;University of Georgia;Massachusetts General Hospital, Harvard University",PhD student;Undergrad student;PhD student;PhD student;PhD student;PhD student;PhD student;Assistant Professor;Associate Professor;Full Professor;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96920,,,https://openreview.net/forum?id=0bINeW40u4,
6,54,0.38273144,-0.19184409,1,0.40562164791490474,-0.08153763996448539,"[8.530849522351533e-05, 0.9996783707977478, 2.0404032846190705e-26, 0.00023632070702880856, 1.5697697423948871e-18]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0cSQ1Sg7db,Generalization of Hamiltonian algorithms,Generalization;stochastic algorithms;concentration inequalities;PAC-Bayes,6.5,3.0,Andreas Maurer,,,https://neurips.cc/virtual/2024/poster/96919,,,https://openreview.net/forum?id=0cSQ1Sg7db,
6,55,-0.029614072,-0.05991212,0,0.043912488447873634,0.0009302794543285151,"[0.9368286088266193, 1.6680130855485847e-05, 4.490576113516171e-10, 0.01290932551492057, 0.050245385078546846]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0cgDDa4OFr,Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation,source distribution estimation;maximum entropy;Sliced-Wasserstein distance;empirical Bayes;simulation-based inference,5.8,2.8,Julius Vetter;Guy Moss;Cornelius Schröder;Richard Gao;Jakob H. Macke,Eberhard-Karls-Universität Tübingen;Eberhard-Karls-Universität Tübingen;University Tübingen;Eberhard-Karls-Universität Tübingen,PhD student;PhD student;Postdoc;Postdoc,https://neurips.cc/virtual/2024/poster/96918,,,https://openreview.net/forum?id=0cgDDa4OFr,/media/PosterPDFs/NeurIPS%202024/96918.png?t=1733318904.6928847
6,56,-0.041920777,-0.1336057,0,0.043912488447873634,0.0009302794543285151,"[0.8167894634672567, 0.00011351820917289787, 9.214887385833025e-14, 0.1646390028110492, 0.0184580155124291]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0d50Il6enG,Non-parametric classification via expand-and-sparsify representation,non-parametric regression;non-parametric classification;expand-and-sparsify representation;universal consistency;minimax-optimal convergence rate,6.0,3.0,Kaushik Sinha,Wichita State University,Associate Professor,https://neurips.cc/virtual/2024/poster/96917,,,https://openreview.net/forum?id=0d50Il6enG,/media/PosterPDFs/NeurIPS%202024/96917.png?t=1731697679.5420048
6,57,-0.05421332,-0.22073112,3,-0.1265023537202139,-0.2905588727955389,"[0.3745593334872136, 0.00038831683375293983, 4.3367526470564185e-19, 0.6236001559469834, 0.0014521937320499802]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,0dtA21q83C,DeNetDM: Debiasing by Network Depth Modulation,Trustworthy Machine Learning;Debiasing;Robustness,6.0,3.5,Silpa Vadakkeeveetil Sreelatha;Adarsh Kappiyath;Abhra Chaudhuri;Anjan Dutta,University of Surrey;University of Exeter;University of Surrey,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96916,,,https://openreview.net/forum?id=0dtA21q83C,/media/PosterPDFs/NeurIPS%202024/96916.png?t=1733689557.490417
6,58,-0.19589648,0.09422963,4,-0.213519426706877,-0.006297675711616576,"[0.012457535006997165, 4.402027617025809e-14, 0.0013782120279371385, 5.9229171563315675e-09, 0.9861642470421046]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0e5uOaJxo1,Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure,Graph Neural Network;Protein Sequence;Structure,5.0,3.3333333333333335,Bozhen Hu;Cheng Tan;Jun Xia;Yue Liu;Lirong Wu;Jiangbin Zheng;Yongjie Xu;Yufei Huang;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University, China;National University of Singapore;Westlake University;Westlake University;Westlake University;Zhejiang University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96915,,,https://openreview.net/forum?id=0e5uOaJxo1,/media/PosterPDFs/NeurIPS%202024/96915.png?t=1730385968.8958924
6,59,0.09615892,0.18102637,0,0.043912488447873634,0.0009302794543285151,"[0.9945477998466963, 1.1352175135576228e-07, 0.005185265288729714, 2.2139295681227593e-08, 0.00026679920352695025]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0feJEykDRx,Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models,spatial-temporal data mining;location-based service;check-in sequence;large language model,5.75,4.0,Letian Gong;Yan Lin;Xinyue Zhang;Yiwen Lu;Xuedi Han;Yichen Liu;Shengnan Guo;Youfang Lin;Huaiyu Wan,Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University,PhD student;PhD student;Undergrad student;Undergrad student;MS student;Associate Professor;Full Professor;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96914,,,https://openreview.net/forum?id=0feJEykDRx,/media/PosterPDFs/NeurIPS%202024/96914.png?t=1731289337.5941467
6,60,-0.013711061,-0.07216554,0,0.043912488447873634,0.0009302794543285151,"[0.9548838767465109, 5.52919263454103e-05, 7.447952521104927e-11, 0.024013313683161654, 0.021047517569502433]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0jld45XGgJ,Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?,neural collapse;deep neural collapse;unconstrained features model;deep unconstrained features model;low-rank bias,6.5,3.75,Peter Súkeník;Christoph H. Lampert;Marco Mondelli,Institute of Science and Technology;Institute of Science and Technology Austria;Institute of Science and Technology Austria,PhD student;Assistant Professor;Professor,https://neurips.cc/virtual/2024/poster/96913,,,https://openreview.net/forum?id=0jld45XGgJ,
6,61,0.49365819,-0.019841706,1,0.40562164791490474,-0.08153763996448539,"[3.936977113867012e-05, 0.9999543631756884, 9.983373430917469e-20, 6.2670531729299054e-06, 4.291641557797045e-22]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0l9yGPTHAU,Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms,Robust Markov decision process;norm;sample complexity;strong duality,6.5,3.0,Pierre Clavier;Laixi Shi;Erwan Le Pennec;Eric Mazumdar;Adam Wierman;Matthieu Geist,"École Polytechnique;California Institute of Technology;Ecole polytechnique;Deparment of Computing + Mathematical Sciences, California Institute of Technology;California Institute of Technology;Google",PhD student;Postdoc;Full Professor;Assistant Professor;Professor;Researcher,https://neurips.cc/virtual/2024/poster/96912,,,https://openreview.net/forum?id=0l9yGPTHAU,
6,62,-0.096782275,0.2680031,2,-0.1175666686646391,0.3253834673790484,"[0.006326202588688208, 1.0824738448449658e-16, 0.9851202647131411, 3.659503829588578e-15, 0.008553532698166935]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,0lBx844upd,ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models,network pruning;unstructured pruning;large language model;ADMM;pre-conditioned conjugate gradient;optimization,5.333333333333333,3.0,Xiang Meng;Kayhan Behdin;Haoyue Wang;Rahul Mazumder,Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology,PhD student;PhD student;PhD student;Associate Professor,https://neurips.cc/virtual/2024/poster/96911,,,https://openreview.net/forum?id=0lBx844upd,/media/PosterPDFs/NeurIPS%202024/96911.png?t=1731079283.0533488
6,63,-0.07022652,-0.30347943,3,-0.1265023537202139,-0.2905588727955389,"[0.19037099208061464, 0.0006661479633860599, 9.543175598276884e-25, 0.8088778678506877, 8.49921053116103e-05]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,0lau89u4oE,Accelerating Non-Maximum Suppression: A Graph Theory Perspective,non-maximum suppression;object detection;graph theory,5.5,3.25,King-Siong Si;Lu Sun;Weizhan Zhang;Tieliang Gong;Jiahao Wang;Jiang Liu;Hao Sun,Xi'an Jiaotong University;Xi'an Jiaotong University;North China University of Technology;China Telecom Corporation Ltd. Data&AI Technology Company,MS student;MS student;MS student;Researcher,https://neurips.cc/virtual/2024/poster/96910,,,https://openreview.net/forum?id=0lau89u4oE,/media/PosterPDFs/NeurIPS%202024/96910.png?t=1733315333.5240822
6,64,-0.08510746,-0.26066056,3,-0.1265023537202139,-0.2905588727955389,"[0.24833534773518484, 0.00019486643873421533, 1.6344935704908495e-21, 0.7506122188576779, 0.0008575669684030419]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,0m19blQT6y,BitsFusion: 1.99 bits Weight Quantization of Diffusion Model,Diffusion;Quantization;Stable Diffusion;Low bit,5.75,4.5,Yang Sui;Yanyu Li;Anil Kag;Yerlan Idelbayev;Junli Cao;Ju Hu;Dhritiman Sagar;Bo Yuan;Sergey Tulyakov;Jian Ren,Rutgers University;Northeastern University;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Rutgers University;Snap Inc.;Snap Inc.,PhD student;PhD student;Researcher;Researcher;Researcher;Researcher;Researcher;Assistant Professor;Director of Research;Research Scientist,https://neurips.cc/virtual/2024/poster/96909,,,https://openreview.net/forum?id=0m19blQT6y,/media/PosterPDFs/NeurIPS%202024/96909.png?t=1729915675.3170154
6,65,-0.00251228,0.3769304,2,-0.1175666686646391,0.3253834673790484,"[0.007128457230265587, 1.2829708090088476e-17, 0.9928502987925845, 2.229354779477705e-19, 2.1243977149922527e-05]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,0mRouJElbZ,ProgressGym: Alignment with a Millennium of Moral Progress,Progress Alignment;AI Alignment;Large Language Models,7.666666666666667,2.6666666666666665,Tianyi Qiu;Yang Zhang;Xuchuan Huang;Jasmine Xinze Li;Jiaming Ji;Yaodong Yang,"University of California, Berkeley;Peking University;Peking University;Peking University;Peking University;Peking University",Intern;Undergrad student;Undergrad student;Intern;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/97875,,,,/media/PosterPDFs/NeurIPS%202024/97875.png?t=1731742041.9348912
6,66,0.42614552,0.08994585,1,0.40562164791490474,-0.08153763996448539,"[0.019723746661553503, 0.9802627085739779, 5.0136564019410025e-12, 1.3544759454821374e-05, 1.6333034770430797e-16]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0nSY8NiILP,Tight Bounds for Learning RUMs from Small Slates,discrete choice;random utility model;approximation theory,6.0,2.75,Flavio Chierichetti;Mirko Giacchini;Ravi Kumar;Alessandro Panconesi;Andrew Tomkins,Sapienza University of Rome;Sapienza University of Rome;Google;Sapienza University of Rome;Google,Full Professor;PhD student;Research Scientist;Full Professor;Researcher,https://neurips.cc/virtual/2024/poster/96908,,,https://openreview.net/forum?id=0nSY8NiILP,/media/PosterPDFs/NeurIPS%202024/96908.png?t=1732698791.0319488
6,67,0.25132486,-0.20319358,1,0.40562164791490474,-0.08153763996448539,"[0.008622341020000262, 0.973296508601126, 2.311316988730736e-23, 0.01808115037581882, 3.054750049002336e-12]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0nzKznCjFG,Private and Personalized Frequency Estimation in a Federated Setting,federated learning;personalization;privacy,5.75,3.0,Amrith Setlur;Vitaly Feldman;Kunal Talwar,Carnegie Mellon University;Apple AI Research;Apple,PhD student;Research Scientist;Research Scientist,https://neurips.cc/virtual/2024/poster/96907,,,https://openreview.net/forum?id=0nzKznCjFG,
6,68,-0.18157998,0.03947093,4,-0.213519426706877,-0.006297675711616576,"[0.02525205470023294, 3.5237373277471276e-12, 1.854889508171255e-05, 5.850617183267508e-07, 0.9747288113394434]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0o7Rd5jngV,Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling,Transformer;expressive power;theoretical insights,6.333333333333333,3.0,Mingze Wang;Weinan E,Peking University;Peking University,PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96906,,,https://openreview.net/forum?id=0o7Rd5jngV,
6,69,-0.12251995,-0.049827244,4,-0.213519426706877,-0.006297675711616576,"[0.31447450302987057, 5.026962090461919e-08, 6.185489104487165e-09, 0.001601232036262339, 0.6839242084787572]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0o9E8AsFgW,DarkSAM: Fooling Segment Anything Model to Segment Nothing,Segment Anything Model;Adversarial Example,6.333333333333333,4.0,Ziqi Zhou;Yufei Song;Minghui Li;Shengshan Hu;Xianlong Wang;Leo Yu Zhang;Dezhong Yao;Hai Jin,Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Griffith University;Huazhong University of Science and Technology;Huazhong University of Science and Technology,PhD student;PhD student;Assistant Professor;Associate Professor;PhD student;Researcher;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96905,,,https://openreview.net/forum?id=0o9E8AsFgW,
6,70,-0.18423451,0.25213403,2,-0.1175666686646391,0.3253834673790484,"[0.0008068369098070447, 2.798715398567098e-19, 0.9724892664248659, 5.7377943995589235e-16, 0.02670389666532639]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,0oUutV92YF,ProtGO: Function-Guided Protein Modeling for Unified Representation Learning,Teacher-student;Knowledge Distillation;Protein Function,5.666666666666667,3.6666666666666665,Bozhen Hu;Cheng Tan;Yongjie Xu;Zhangyang Gao;Jun Xia;Lirong Wu;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University;Westlake University, China;Westlake University, China;Westlake University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96904,,,https://openreview.net/forum?id=0oUutV92YF,/media/PosterPDFs/NeurIPS%202024/96904.png?t=1730386167.5899446
6,71,-0.04843812,0.4040603,2,-0.1175666686646391,0.3253834673790484,"[0.0011148546323405172, 1.689211984354443e-20, 0.9988697629674493, 5.962957943252164e-22, 1.5382400210052093e-05]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,0og7nmvDbe,Confidence Regulation Neurons in Language Models,LLMs;Interpretability;Mechanistic Interpretability,7.0,3.75,Alessandro Stolfo;Ben Peng Wu;Wes Gurnee;Yonatan Belinkov;Xingyi Song;Mrinmaya Sachan;Neel Nanda,"ETHZ - ETH Zurich;University of Sheffield;Massachusetts Institute of Technology;Technion, Technion;University of Sheffield;Google DeepMind;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Assistant Professor;Lecturer;Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96903,,,https://openreview.net/forum?id=0og7nmvDbe,
6,72,0.25011468,-0.18353273,1,0.40562164791490474,-0.08153763996448539,"[0.012879506487610206, 0.966044812713686, 5.178818322016368e-22, 0.021075680790659124, 8.044747347121853e-12]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0qb8KoPsej,Accelerating Matroid Optimization through Fast Imprecise Oracles,matroid optimization;weak-strong models;learning-augmented algorithms;algorithms with predictions;query minimization;robustness,5.5,2.75,Franziska Eberle;Felix Hommelsheim;Alexander Lindermayr;Zhenwei Liu;Nicole Megow;Jens Schlöter,Technische Universität Berlin;Universität Bremen;Universität Bremen;Universität Bremen;Universität Bremen,Postdoc;Postdoc;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96902,,,https://openreview.net/forum?id=0qb8KoPsej,
6,73,0.24778247,-0.18444899,1,0.40562164791490474,-0.08153763996448539,"[0.013791646643944071, 0.9635126459340477, 5.256746284485856e-22, 0.022695707412076695, 9.931492513386956e-12]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0rl5vWOzRU,Score-Optimal Diffusion Schedules,Diffusion model;adaptive schedule;Annealed Langevin,6.0,3.0,Christopher Williams;Andrew Campbell;Arnaud Doucet;Saifuddin Syed,University of Oxford;University of Oxford;University of Oxford;University of Oxford,PhD student;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96901,,,https://openreview.net/forum?id=0rl5vWOzRU,
6,74,-0.17648138,-0.41862112,3,-0.1265023537202139,-0.2905588727955389,"[0.17612940699360552, 7.23376757645741e-05, 1.7598586241528892e-32, 0.8237834208219654, 1.4834508664443495e-05]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,0sJBW05a2W,3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration,Point Cloud Registration;Focus and Matching,5.666666666666667,4.333333333333333,Liyuan Zhang;Le Hui;qi liu;Bo Li;Yuchao Dai,Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwestern Polytechnical University Xi'an;Northwestern Polytechnical University,MS student;Associate Professor;Researcher;Associate Professor;Professor,https://neurips.cc/virtual/2024/poster/96900,,,https://openreview.net/forum?id=0sJBW05a2W,/media/PosterPDFs/NeurIPS%202024/96900.png?t=1731333373.8074756
6,75,-0.16704087,-0.3598848,3,-0.1265023537202139,-0.2905588727955389,"[0.13644072661186113, 3.261443301040739e-05, 5.113764798523792e-28, 0.8633953664122741, 0.00013129254285434988]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,0sycTGl4In,4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization,Dynamic Novel View Synthesis;4D Gaussian splatting;Sparse reconstruction;in-the-wild,5.333333333333333,4.666666666666667,Mijeong Kim;Jongwoo Lim;Bohyung Han,Seoul National University;Seoul National University,Full Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96899,,,https://openreview.net/forum?id=0sycTGl4In,/media/PosterPDFs/NeurIPS%202024/96899.png?t=1733712090.5881364
6,76,0.61073065,0.018717432,1,0.40562164791490474,-0.08153763996448539,"[1.0036198545608218e-06, 0.9999988556187451, 1.4915439357828173e-21, 1.4076140018491647e-07, 7.547785862452615e-29]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,0uGlKYS7a2,Maximizing utility in multi-agent environments by anticipating the behavior of other learners,Game Theory; no regret; learning theory;,5.5,3.25,Angelos Assos;Yuval Dagan;Constantinos Costis Daskalakis,Massachusetts Institute of Technology;Massachusetts Institute of Technology,MS student;Full Professor,https://neurips.cc/virtual/2024/poster/96898,,,https://openreview.net/forum?id=0uGlKYS7a2,/media/PosterPDFs/NeurIPS%202024/96898.png?t=1731753379.9098587
6,77,-0.07488669,0.3827278,2,-0.1175666686646391,0.3253834673790484,"[0.000597156407873587, 9.531420682412268e-21, 0.9993592025471164, 2.3069957227606344e-21, 4.3641045009932214e-05]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,0uXtFk5KNJ,BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models,block coordinate descent;large language models,5.25,3.75,Qijun Luo;Hengxu Yu;Xiao Li,"The Chinese University of Hong Kong, Shenzhen;The Chinese University of Hong Kong, Shenzhen;Chinese University of Hong Kong Shen Zhen",PhD student;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96897,,,https://openreview.net/forum?id=0uXtFk5KNJ,/media/PosterPDFs/NeurIPS%202024/96897.png?t=1733743857.9232197
6,78,0.022653038,0.24370801,2,-0.1175666686646391,0.3253834673790484,"[0.4393114803957601, 2.7150695675687316e-11, 0.5570263099498451, 1.663598209400821e-11, 0.003662209610608]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,0zFVhMBZHJ,Mixture of Tokens: Continuous MoE through Cross-Example Aggregation,LLM;Mixture of Experts;MoE;conditional computation;fully-differentiable;language modeling,6.0,3.6666666666666665,Szymon Antoniak;Michał Krutul;Maciej Pióro;Jakub Krajewski;Jan Ludziejewski;Kamil Ciebiera;Krystian Król;Tomasz Odrzygóźdź;Marek Cygan;Sebastian Jaszczur,IDEAS NCBR Sp.;IDEAS NCBR Sp.;University of Warsaw;University of Warsaw;IDEAS NCBR Sp.;University of Warsaw;IDEAS NCBR;Nomagic;University of Warsaw,PhD student;Researcher;PhD student;PhD student;Intern;MS student;Postdoc;Founder / CTO;PhD student,https://neurips.cc/virtual/2024/poster/96896,,,https://openreview.net/forum?id=0zFVhMBZHJ,/media/PosterPDFs/NeurIPS%202024/96896.png?t=1730308223.324062
6,79,0.24368975,0.18879418,0,0.043912488447873634,0.0009302794543285151,"[0.9998081449774141, 0.00013027854549962266, 6.145736923406972e-05, 1.0335934026580103e-07, 1.5748511873174224e-08]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,0zWzJj6lO3,Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents,cooperative AI;AI safety;LLM agents;cognitive science;language model evaluation;dynamic evaluation;alignment;agency;evolving benchmarks;multi-agent interactions,5.75,3.5,Giorgio Piatti;Zhijing Jin;Max Kleiman-Weiner;Bernhard Schölkopf;Mrinmaya Sachan;Rada Mihalcea,Common Sense Machines;University of Michigan;Swiss Federal Institute of Technology,Principal Researcher;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96895,,,https://openreview.net/forum?id=0zWzJj6lO3,
6,80,-0.16938657,-0.05973538,4,-0.213519426706877,-0.006297675711616576,"[0.11188399852269354, 2.95768598594209e-09, 2.6779099936457076e-09, 0.0007043446954015291, 0.8874116511463089]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,0zfUiSX5si,AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases,De Novo Peptide sequencing;Proteomics;Mass Spectrum,5.333333333333333,3.0,Jun Xia;Shaorong Chen;Jingbo Zhou;Xiaojun Shan;Wenjie Du;Zhangyang Gao;Cheng Tan;Bozhen Hu;Jiangbin Zheng;Stan Z. Li,"Westlake University, China;Westlake University;Jilin University;University of Electronic Science and Technology of China;University of Science and Technology of China;Westlake University, China;Zhejiang University & Westlake University;Westlake University;Westlake University;Westlake University",PhD student;PhD student;Undergrad student;Undergrad student;Assistant Professor;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96894,,,https://openreview.net/forum?id=0zfUiSX5si,
6,81,-0.25151917,-0.28693447,3,-0.1265023537202139,-0.2905588727955389,"[0.1530004173332469, 2.556421757190788e-07, 9.95938808057924e-22, 0.8293261878703151, 0.0176731391542622]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,105ZuvpdyW,SegVol: Universal and Interactive Volumetric Medical Image Segmentation,Volumetric Medical Image Segmentation;3D Segmentation Foundation Model;Universal and Interactive 3D Segmentation,7.666666666666667,4.333333333333333,Yuxin Du;Fan BAI;Tiejun Huang;Bo Zhao,Beijing Academy of Artificial Intelligence;The Chinese University of Hong Kong;Peking University;BAAI,Intern;PhD student;Full Professor;Principal Researcher,https://neurips.cc/virtual/2024/poster/96893,,,https://openreview.net/forum?id=105ZuvpdyW,/media/PosterPDFs/NeurIPS%202024/96893.png?t=1731410503.871179
6,82,0.04577409,-0.24324691,3,-0.1265023537202139,-0.2905588727955389,"[0.28509068050100167, 0.02703324587013926, 8.224761760093175e-22, 0.6878691340586262, 6.939570232838767e-06]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,1067784F6e,Data Distribution Valuation,Data distribution valuation;Huber model;Maximum mean discrepancy,6.333333333333333,4.333333333333333,Xinyi Xu;Shuaiqi Wang;Chuan-Sheng Foo;Bryan Kian Hsiang Low;Giulia Fanti,"National University of Singapore;Carnegie Mellon University;Institute for Infocomm Research, A*STAR;National University of Singapore;Carnegie Mellon University",PhD student;PhD student;Principal Scientist;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96892,,,https://openreview.net/forum?id=1067784F6e,/media/PosterPDFs/NeurIPS%202024/96892.png?t=1731176029.7581189
6,83,-0.22563006,-0.049784996,4,-0.213519426706877,-0.006297675711616576,"[0.024545590549472945, 2.8193092267336534e-11, 8.06789674301511e-09, 7.038051867583886e-05, 0.9753840208357613]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,12A1RT1L87,Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?,Dataset Condensation;Dataset Distillation,5.666666666666667,3.6666666666666665,Lingao Xiao;Yang He,"School of Computer Science and  Engineering, Nanyang Technological University;Institute of High Performance Computing, Singapore, A*STAR",Undergrad student;Researcher,https://neurips.cc/virtual/2024/poster/96891,,,https://openreview.net/forum?id=12A1RT1L87,/media/PosterPDFs/NeurIPS%202024/96891.png?t=1731138766.8349779
6,84,-0.20074943,0.040258985,4,-0.213519426706877,-0.006297675711616576,"[0.015036487144731632, 7.602516637030285e-13, 2.031547641136626e-05, 2.823855345855364e-07, 0.9849429149925624]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,135eKqDoRR,Bayesian-guided Label Mapping for Visual Reprogramming,visual reprogramming;adversarial reprogramming;output label mapping;Bayesian probability,7.25,4.0,Chengyi Cai;Zesheng Ye;Lei Feng;Jianzhong Qi;Feng Liu,University of Melbourne;Singapore University of Technology and Design;University of Melbourne;University of Melbourne,PhD student;Assistant Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96890,,,https://openreview.net/forum?id=135eKqDoRR,
6,85,-0.1496939,0.30529067,2,-0.1175666686646391,0.3253834673790484,"[0.00032184329887018293, 1.9374607986342186e-20, 0.9978924896194884, 1.7313897169526725e-18, 0.0017856670816415422]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,14hLJr6kZ3,Enhancing Domain Adaptation through Prompt Gradient Alignment,transfer learning; domain adaptation; prompt-tuning,6.25,3.25,Hoang Phan;Tung Lam Tran;Quyen Tran;Trung Le,VinAi Research;VinAI Research;Monash University;New York University,Research resident;Research Resident;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96889,,,https://openreview.net/forum?id=14hLJr6kZ3,/media/PosterPDFs/NeurIPS%202024/96889.png?t=1732036918.0147438
6,86,0.2630342,0.051892787,0,0.043912488447873634,0.0009302794543285151,"[0.8742828140060043, 0.12504939907854046, 2.6768206771464742e-09, 0.0006677792987788317, 4.939855977344408e-09]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,15460JjocO,Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners,multi-agent;reinforcement learning;robustness;diversity;specialization,7.0,3.6666666666666665,Rujikorn Charakorn;Poramate Manoonpong;Nat Dilokthanakul,Sakana AI;Vidyasirimedhi Institute of Science and Technology;King Mongkut's Institute of Technology Ladkrabang,Intern;Full Professor;Lecturer,https://neurips.cc/virtual/2024/poster/96888,,,https://openreview.net/forum?id=15460JjocO,/media/PosterPDFs/NeurIPS%202024/96888.png?t=1731395258.7214391
6,87,0.61719507,-0.024593957,1,0.40562164791490474,-0.08153763996448539,"[2.8741979100539586e-07, 0.9999995413147902, 6.743464981846148e-24, 1.7126541907134884e-07, 8.763800234532152e-30]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,15Jm9v7wCo,No-Regret Learning for Fair Multi-Agent Social Welfare Optimization,Online Learning;Nash Social Welfare,5.666666666666667,3.3333333333333335,Mengxiao Zhang;Ramiro Deo-Campo Vuong;Haipeng Luo,University of Southern California;University of Southern California,Undergrad student;Associate Professor,https://neurips.cc/virtual/2024/poster/96887,,,https://openreview.net/forum?id=15Jm9v7wCo,
6,88,-0.14552048,-0.15470643,0,0.043912488447873634,0.0009302794543285151,"[0.5444821891695393, 1.6191793472426508e-06, 6.605797999465584e-14, 0.1573262081395287, 0.29818998351151876]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,15PS30UOUp,Kuro Siwo: 33 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping,Synthetic Aperture Radar;SAR;Deep Learning;Remote Sensing;Floods;dataset,6.75,3.75,Nikolaos Ioannis Bountos;Maria Sdraka;Angelos Zavras;Andreas Karavias;Ilektra Karasante;Themistocles Herekakis;Angeliki Thanasou;Dimitrios Michail;Ioannis Papoutsis,National Observatory of Athens;National Observatory of Athens;Harokopio University;The Centre for Research & Technology;National Observatory of Athens ;National Observatoty of Athens;National Observatory of Athens;Harokopio University;National Technical University of Athens,PhD student;Researcher;PhD student;Researcher;Researcher;Researcher;Researcher;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97874,,,,
6,89,0.004352061,-0.07103703,0,0.043912488447873634,0.0009302794543285151,"[0.9646930825006802, 0.0001206523819201877, 5.0968635247430724e-11, 0.025638507219764857, 0.009547757846666116]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,164QnJsYjF,Dense Associative Memory Through the Lens of Random Features,Associative Memory;Kernels;Random Features;Hopfield Network,6.0,3.0,Benjamin Hoover;Duen Horng Chau;Hendrik Strobelt;Parikshit Ram;Dmitry Krotov,International Business Machines;International Business Machines;International Business Machines;Massachusetts Institute of Technology;Georgia Institute of Technology,AI Research Engineer;Principal Researcher;Principal Researcher;Researcher;Full Professor,https://neurips.cc/virtual/2024/poster/96886,,,https://openreview.net/forum?id=164QnJsYjF,/media/PosterPDFs/NeurIPS%202024/96886.png?t=1733846086.053208
6,90,-0.31772932,0.41427824,2,-0.1175666686646391,0.3253834673790484,"[1.7372350770832777e-07, 6.193531801589144e-32, 0.9999907653902658, 1.1895437773718083e-28, 9.060886226261435e-06]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,168NLzTpw8,Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation,Vision-Language;Region-Level Understanding;Multimodal Large Language Model,5.75,3.75,Yaoyuan Liang;Zhuojun Cai;Jian Xu;Guanbo Huang;Yiran Wang;Xiao Liang;Jiahao Liu;Ziran Li;Jingang Wang;Shao-Lun Huang,"Tsinghua Shenzhen International Graduate School, Tsinghua University;Microsoft;University of Electronic Science and Technology of China;Tsinghua University;Tsinghua University;Meituan;Meituan;Tsinghua University",PhD student;Intern;Undergrad student;MS student;MS student;Researcher;Researcher;Associate Professor,https://neurips.cc/virtual/2024/poster/96885,,,https://openreview.net/forum?id=168NLzTpw8,
6,91,-0.118134014,0.26676714,2,-0.1175666686646391,0.3253834673790484,"[0.003406305870667776, 1.8872648172636503e-17, 0.986078815408606, 1.586113671892648e-15, 0.010514878720724754]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,181llen2gw,A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks,Vision-Language Model;Fairness;Debias,6.333333333333333,3.6666666666666665,Hoin Jung;Taeuk Jang;Xiaoqian Wang,Purdue University;Purdue University;Purdue University,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96884,,,https://openreview.net/forum?id=181llen2gw,/media/PosterPDFs/NeurIPS%202024/96884.png?t=1731379505.2628894
6,92,-0.19037005,0.30377576,2,-0.1175666686646391,0.3253834673790484,"[9.512189696715574e-05, 5.867638541419862e-22, 0.9979307592677906, 3.039282075175862e-19, 0.0019741188352424004]","[0.009973648048490982, 0.0038217999098212347]",0.17378235928912458,18FGRNd0wZ,Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation,tokenization of crystals;language models;materials generation,6.0,3.5,Keqiang Yan;Xiner Li;Hongyi Ling;Kenna Ashen;Carl Edwards;Raymundo Arroyave;Marinka Zitnik;Heng Ji;Xiaofeng Qian;Xiaoning Qian;Shuiwang Ji,"Texas A&M University;Texas A&M University - College Station;Texas A&M University - College Station;Texas A&M University - College Station;Genentech;Texas A&M University Main Campus;Harvard University;University of Illinois, Urbana-Champaign;Texas A&M University;Texas A&M;Texas A&M University",PhD student;PhD student;PhD student;PhD student;Intern;Assistant Professor;Full Professor;Associate Professor;Full Professor;Professor,https://neurips.cc/virtual/2024/poster/96883,,,https://openreview.net/forum?id=18FGRNd0wZ,/media/PosterPDFs/NeurIPS%202024/96883.png?t=1733428872.6393995
6,93,-0.18803668,0.09546091,4,-0.213519426706877,-0.006297675711616576,"[0.015371885805050492, 7.662106283052505e-14, 0.0014944223862081963, 7.227416413779675e-09, 0.9831336845812483]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,18RdkSv9h9,FINALLY: fast and universal speech enhancement with studio-like quality,speech enhancement; generative models,6.5,4.75,Nicholas Babaev;Kirill Tamogashev;Azat Saginbaev;Ivan Shchekotov;Hanbin Bae;Hosang Sung;WonJun Lee;Hoon-Young Cho;Pavel Andreev,"Samsung;Skolkovo Institute of Science and Technology;Moscow Institute of Physics and Technology;Samsung;Samsung;Samsung;Higher School of Economics, Higher School of Economics",Researcher;MS student;MS student;Principal Researcher;Researcher;Vice President;MS student,https://neurips.cc/virtual/2024/poster/96882,,,https://openreview.net/forum?id=18RdkSv9h9,/media/PosterPDFs/NeurIPS%202024/96882.png?t=1731683595.700073
6,94,0.32727078,-0.11709024,1,0.40562164791490474,-0.08153763996448539,"[0.0027124965940664935, 0.9954412661126872, 4.560678905687931e-20, 0.0018462372932256273, 2.062356688608524e-14]","[0.015649291601961005, 0.01214128732351877]",0.18526842627541115,1ATLLgvURu,Learning-Augmented Priority Queues,learning-augmented algorithms;algorithms with predictions;priority queue;shortest paths;Dijkstra,5.75,4.25,Ziyad Benomar;Christian Coester,University of Oxford,Associate Professor,https://neurips.cc/virtual/2024/poster/96881,,,https://openreview.net/forum?id=1ATLLgvURu,
6,95,0.3095995,0.5030761,0,0.043912488447873634,0.0009302794543285151,"[0.9980997368486848, 1.3615744610719732e-11, 0.0019002631376289364, 1.1326004960789296e-20, 7.025404712783085e-14]","[0.018526594330651982, 0.030452144566032895]",0.27224736026991364,1BZKqZphsW,Risk-Averse Fine-tuning of Large Language Models,Risk Averse Reinforcement Learning;Large Language Model Finetuning,5.8,3.2,Sapana Chaudhary;Ujwal Dinesha;Dileep Kalathil;Srinivas Shakkottai,Texas A&M University;Texas A&M University - College Station;Texas A&M University;Texas A&M,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96880,,,https://openreview.net/forum?id=1BZKqZphsW,/media/PosterPDFs/NeurIPS%202024/96880.png?t=1733328781.5713553
6,96,-0.26364937,-0.38828564,3,-0.1265023537202139,-0.2905588727955389,"[0.09480270861829877, 9.197875746670924e-07, 2.0260156780135998e-29, 0.9050022598683538, 0.0001941117257728778]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,1CssOqRYyz,Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds,compression;point cloud;diffusion,4.0,4.0,Kai Liu;Kang You;Pan Gao,"Nanjing University of Aeronautics and Astronautics;Nanjing university;Nanjing University of Aeronautics and Astronautics, Tsinghua University",MS student;PhD student;Associate Professor,,,,,
6,97,-0.25224024,-0.31188005,3,-0.1265023537202139,-0.2905588727955389,"[0.12173357772710983, 3.697774755827373e-07, 1.33286948358601e-23, 0.8728045647690309, 0.005461487726383704]","[0.01607136829354227, 0.006720631658228496]",0.13850241350370915,1Du3mMP5YN,Learning to Shape In-distribution Feature Space for Out-of-distribution Detection,Out-of-distribution Detection,5.75,4.0,Yonggang Zhang;Jie Lu;Bo Peng;Zhen Fang;Yiu-ming Cheung,Hong Kong Baptist University;University of Technology Sydney;University of Technology Sydney,Postdoc;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96879,,,https://openreview.net/forum?id=1Du3mMP5YN,/media/PosterPDFs/NeurIPS%202024/96879.png?t=1731745181.7993424
6,98,-0.30068702,-0.14781809,4,-0.213519426706877,-0.006297675711616576,"[0.04633000836568957, 9.369522109901297e-11, 7.535687381097204e-13, 0.00759473257288932, 0.9460752589669723]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,1ELFGSNBGC,Multiview Scene Graph,scene representation; spatial understanding; place recognition; object correspondence; scene graph,5.25,3.25,Juexiao Zhang;Gao Zhu;Sihang Li;Xinhao Liu;Haorui Song;Xinran Tang;Chen Feng,New York University;New York University;New York University;New York University;New York University;New York University;New York University,PhD student;MS student;PhD student;PhD student;MS student;MS student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96878,,,https://openreview.net/forum?id=1ELFGSNBGC,/media/PosterPDFs/NeurIPS%202024/96878.png?t=1731728482.5838113
6,99,-0.09486352,0.005280091,4,-0.213519426706877,-0.006297675711616576,"[0.3736718816326427, 2.0106795570950277e-08, 9.65420804459086e-07, 0.00013347835616778388, 0.6261936544835894]","[0.00532382814540541, 0.007258672542561898]",0.23019944066184153,1F32iCJFfa,Schrodinger Bridge Flow for Unpaired Data Translation,unpaired data translation;diffusion models;Schrodinger bridge;bridge matching;stochastic interpolant;flow matching,6.5,4.0,Valentin De Bortoli;Iryna Korshunova;Andriy Mnih;Arnaud Doucet,University of Oxford;Google DeepMind;Google DeepMind;University of Oxford,Postdoc;Researcher;Research Scientist;Full Professor,https://neurips.cc/virtual/2024/poster/96877,,,https://openreview.net/forum?id=1F32iCJFfa,/media/PosterPDFs/NeurIPS%202024/96877.png?t=1731688420.732189
7,0,0.08799766,-0.06060414,0,0.08273747157300083,0.016519931061773654,"[0.8494366135196633, 0.011412833749839455, 4.017591118007274e-11, 0.1376707456949014, 0.0014798069954201924]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,00Sx577BT3,The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning,numerical simulations;fluid-dynamics;partial differential equations;operator learning,6.666666666666667,3.6666666666666665,Ruben Ohana;Michael McCabe;Lucas Thibaut Meyer;Rudy Morel;Fruzsina Julia Agocs;Miguel Beneitez;Marsha Berger;Blakesley Burkhart;Stuart B. Dalziel;Drummond Buschman Fielding;Daniel Fortunato;Jared A. Goldberg;Keiya Hirashima;Yan-Fei Jiang;Rich Kerswell;Suryanarayana Maddu;Jonah M. Miller;Payel Mukhopadhyay;Stefan S. Nixon;Jeff Shen;Romain Watteaux;Bruno Régaldo-Saint Blancard;François Rozet;Liam Holden Parker;Miles Cranmer;Shirley Ho,"Flatiron Institute;University of Colorado, Boulder;INRIA;Flatiron Institute;Flatiron Institute;University of Cambridge;Flatiron Institute;Rutgers University;University of Cambridge;Simons Foundation;Flatiron Institute;Flatiron Institute;Simons Foundation;University of Cambridge;Flatiron Institute/Simons Foundation;Los Alamos National Laboratory;University of California, Berkeley;University of Cambridge;Princeton University;CEA;Flatiron Institute;Flatiron Institute;Flatiron Institute;University of Cambridge;Carnegie Mellon University;The University of Tokyo",Postdoc;PhD student;PhD student;Postdoc;Postdoc;Postdoc;Full Professor;Assistant Professor;Director of the GK Batchelor Laboratory;Postdoc;Researcher;Postdoc;Researcher;Full Professor;Postdoc;Researcher;Postdoc;PhD student;PhD student;Researcher;Postdoc;Intern;Researcher;Assistant Professor;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/97882,,,,
7,1,-0.08406016,0.2851326,2,-0.11663928851106392,0.32384781611338126,"[0.0010471284149607433, 1.2068916573184135e-14, 0.9971495638664118, 4.6269419530810484e-07, 0.0018028450244202715]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,00uVk06eVK,On the Noise Robustness of In-Context Learning for Text Generation,In-Context Learning;Large Language Models;Noise Robustness,6.333333333333333,3.0,Hongfu Gao;Feipeng Zhang;Wenyu Jiang;Jun Shu;Feng Zheng;Hongxin Wei,Xi'an Jiaotong University;Xi'an Jiaotong University;Nanjing University;Xi'an Jiaotong University;Southern University of Science and Technology;Southern University of Science and Technology,MS student;Full Professor;PhD student;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96962,,,https://openreview.net/forum?id=00uVk06eVK,/media/PosterPDFs/NeurIPS%202024/96962.png?t=1731587881.4159098
7,2,-0.16364236,-0.11411294,4,-0.1996801020901614,0.0024864258082550324,"[0.06206644111125619, 2.782595453328941e-06, 2.9202345561012487e-11, 0.3394380718051253, 0.5984927044589626]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,01I55gys19,Few-Class Arena: A Benchmark for Efficient Vision Model Selection and Dataset Difficulty,few-class;efficiency;neural network;convolutional neural network;transformer;dataset difficulty measurement;scaling law,5.0,3.3333333333333335,Bryan Bo Cao;Lawrence O'Gorman;Michael Coss;Shubham Jain,Nokia networks GmbH;State University of New York at Stony Brook,Intern;Assistant Professor,,,,,
7,3,0.07371062,-0.27021888,0,0.08273747157300083,0.016519931061773654,"[0.4331289310056252, 0.2630518244030756, 6.468467017849792e-23, 0.30381826220198377, 9.823893155031198e-07]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,01XV5Za56k,Testing Calibration in Nearly-Linear Time,Calibration;Property testing;Linear programming,6.25,3.25,Lunjia Hu;Arun Jambulapati;Kevin Tian;Chutong Yang,Stanford University;Stanford University;Stanford University;University of Texas at Austin,PhD student;PhD student;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96961,,,https://openreview.net/forum?id=01XV5Za56k,
7,4,-0.1284643,0.3103237,2,-0.11663928851106392,0.32384781611338126,"[6.602130435715058e-05, 4.2649905856509234e-17, 0.9995321783991551, 2.3297820090492894e-08, 0.00040177699866768323]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,01lhHg8H9p,GLBench: A Comprehensive Benchmark for Graph with Large Language Models,Graph learning;Large Language Model;Zero-Shot,6.75,4.0,Yuhan Li;Peisong Wang;Xiao Zhu;Aochuan Chen;Haiyun Jiang;Deng Cai;Victor Wai Kin Chan;Jia Li,"Hong Kong University of Science and Technology;Tsinghua University;Beijing University of Posts and Telecommunications;Hong Kong University of Science and Technology;Tencent AI Lab;Tencent AI Lab;Shenzhen International Graduate School, Tsinghua University;Hong Kong University of Science and Technology",PhD student;MS student;Undergrad student;PhD student;Researcher;Research Scientist;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97881,,,,/media/PosterPDFs/NeurIPS%202024/97881.png?t=1731478194.2539835
7,5,-0.23808402,0.26056772,2,-0.11663928851106392,0.32384781611338126,"[2.8488391218698686e-06, 1.9057574778136644e-18, 0.9955144565806181, 2.8279522783319303e-08, 0.004482666300737095]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,01qa1ZJs65,Bridge the Modality and Capability Gaps in Vision-Language Model Selection,Vision-Language Model;Model Selection;Zero-Shot Image Classification,5.25,4.0,Chao Yi;Yuhang He;De-Chuan Zhan;Han-Jia Ye,Nanjing University;Nanjing University;Nanjing University;Nanjing University,MS student;Undergrad student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96960,,,https://openreview.net/forum?id=01qa1ZJs65,/media/PosterPDFs/NeurIPS%202024/96960.png?t=1731123927.9174762
7,6,-0.10493148,-0.30384988,3,-0.13817844936362567,-0.24997137110223888,"[0.16850428375496157, 0.0012015520561795715, 2.1448308145693183e-23, 0.8302347792182462, 5.9384970612616585e-05]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,01s5ODIHKd,FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space,deep watermarking;latent frequency optimization,5.5,3.75,YiYang Guo;Ruizhe Li;Mude Hui;Hanzhong Allan Guo;Chen Zhang;Chuangjian Cai;Le Wan;Shangfei Wang,"University of Science and Technology of China;University of California, Santa Cruz;Renmin University of China;Tsinghua University;University of Science and Technology of China;University of Science and Technology of China",MS student;PhD student;MS student;PhD student;Full Professor;PhD student,https://neurips.cc/virtual/2024/poster/96959,,,https://openreview.net/forum?id=01s5ODIHKd,/media/PosterPDFs/NeurIPS%202024/96959.png?t=1730176108.8718698
7,7,-0.295713,-0.42771262,3,-0.13817844936362567,-0.24997137110223888,"[0.01711432192826241, 1.0112541496335804e-05, 3.2207589530970334e-31, 0.9828743680276363, 1.1975026049482675e-06]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,02CIZ8qeDc,PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection,3D anomaly detection;Zero-shot 3D anomaly detection,6.0,3.6666666666666665,Qihang Zhou;Jiangtao Yan;Shibo He;Wenchao Meng;Jiming Chen,Zhejiang University;Zhejiang University;Zhejiang University;Zhejiang University,PhD student;MS student;Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96958,,,https://openreview.net/forum?id=02CIZ8qeDc,/media/PosterPDFs/NeurIPS%202024/96958.png?t=1731476864.9817398
7,8,-0.3188932,-0.023905918,4,-0.1996801020901614,0.0024864258082550324,"[4.280155359960798e-05, 4.5944650427040734e-12, 2.998156692335022e-07, 0.0011873327376609728, 0.9987695658884758]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,02HWT9c4Lp,Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion,Semantic Scene completion，Voxel Proposal，Knowledge Distillation,5.5,4.0,Lubo Wang;Di Lin;Kairui Yang;Ruonan Liu;Qing Guo;Wuyuan Xie;Miaohui Wang;Lingyu Liang;Yi Wang;Ping Li,"Tianjin University;Tianjin University;Tianjin University;Tianjin University; Agency for Science, Technology and Research (A*STAR));Department of Software Engineering, Shenzhen University;Shenzhen University;South China University of Technology;Shenzhen University;The Hong Kong Polytechnic University",MS student;Associate Professor;PhD student;Associate Professor;Researcher;Associate Professor;Associate Professor;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96957,,,https://openreview.net/forum?id=02HWT9c4Lp,/media/PosterPDFs/NeurIPS%202024/96957.png?t=1731159292.6143699
7,9,0.52375084,0.03593809,1,0.392824477738228,-0.0839010650724529,"[4.966555182360889e-06, 0.9999949572750995, 3.423327895658381e-17, 7.61697182234782e-08, 2.3252010213819677e-17]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,02r24A8doi,Achieving Constant Regret in Linear Markov Decision Processes,Reinforcement learning;Constant regret;Misspecified linear MDP,5.25,2.75,Weitong Zhang;Zhiyuan Fan;Jiafan He;Quanquan Gu,"Massachusetts Institute of Technology;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles",PhD student;PhD student;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96956,,,https://openreview.net/forum?id=02r24A8doi,
7,10,-0.24769914,0.06194072,4,-0.1996801020901614,0.0024864258082550324,"[0.00015988463388257572, 2.189598598392592e-12, 0.00020579058942581094, 0.0002757960934805023, 0.9993585286810216]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,04EC4ZnZJj,MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers,transformer architecture;large language model;computational complexity reduction,6.0,3.5,Ning Ding;Yehui Tang;Haochen Qin;Zhenli Zhou;Chao Xu;Lin Li;Kai Han;Liao Heng;Yunhe Wang,"Peking University;Huawei Technologies Ltd.;Huawei Technologies Ltd.;Peking University;Peking University;Huawei Noah's Ark Lab;, Tsinghua University;Huawei Noah's Ark Lab",PhD student;Researcher;Researcher;MS student;Full Professor;Principal Researcher;Principal Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96955,,,https://openreview.net/forum?id=04EC4ZnZJj,
7,11,0.45866024,0.07679337,1,0.392824477738228,-0.0839010650724529,"[0.0006267777599190855, 0.9993696498911798, 3.1090947841382875e-13, 3.5723484969727494e-06, 9.309177603258187e-14]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,06JRFVK88O,Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games,Multi-agent Reinforcement Learning;Imitation Learning,6.666666666666667,3.0,The Viet Bui;Tien Anh Mai;Thanh Hong Nguyen,Singapore Management University;University of Oregon;Singapore Management University,Assistant Professor;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96954,,,https://openreview.net/forum?id=06JRFVK88O,/media/PosterPDFs/NeurIPS%202024/96954.png?t=1731744891.8886228
7,12,-0.21952832,-0.2596673,3,-0.13817844936362567,-0.24997137110223888,"[0.033942285346511024, 1.2000213073292476e-05, 2.0791550567324348e-19, 0.9594204984887149, 0.006625215951700676]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,06Vt6f2js7,SyncTweedies: A General Generative Framework Based on Synchronized Diffusions,Diffusion Models;Synchronization;Texturing;3D Gaussian Splatting;Mesh;Panorama,6.666666666666667,3.6666666666666665,Jaihoon Kim;Juil Koo;Kyeongmin Yeo;Minhyuk Sung,KAIST;Adobe Systems;Korea Advanced Institute of Science & Technology;Korea Advanced Institute of Science & Technology,MS student;Intern;Undergrad student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96953,,,https://openreview.net/forum?id=06Vt6f2js7,
7,13,0.5387558,-0.021885695,1,0.392824477738228,-0.0839010650724529,"[4.1659294915229314e-07, 0.9999995658440886, 1.9153610979497836e-20, 1.756296235027237e-08, 5.943013930464366e-19]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,07N0qoaZ2L,Improved Analysis for Bandit Learning in Matching Markets,Bandits;Matching markets;Stable matching;Stable regret;Exploration and exploitation;$\alpha$-condition,5.5,3.0,Fang Kong;Zilong Wang;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;John Hopcroft Center, Shanghai Jiao Tong University",PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96952,,,https://openreview.net/forum?id=07N0qoaZ2L,/media/PosterPDFs/NeurIPS%202024/96952.png?t=1731746661.9360106
7,14,-0.31746334,-0.03755091,4,-0.1996801020901614,0.0024864258082550324,"[5.988690447605489e-05, 1.0833836446453527e-11, 9.061308266098242e-08, 0.0019581446148290746, 0.9979818778567783]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,08A6X7FSTs,Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text,Text-to-3D Scene Generation;Latent Diffusion Models,5.5,4.5,Xinyang Li;Zhangyu Lai;Linning Xu;Yansong Qu;Liujuan Cao;Shengchuan Zhang;Bo Dai;Rongrong Ji,Xiamen University;Xiamen University;Xiamen University;Xiamen University;Xiamen University;Shanghai AI Laboratory;Xiamen University;The Chinese University of Hong Kong,PhD student;MS student;PhD student;Full Professor;Assistant Professor;Scientist;Full Professor;Ph.D. student,https://neurips.cc/virtual/2024/poster/96951,,,https://openreview.net/forum?id=08A6X7FSTs,/media/PosterPDFs/NeurIPS%202024/96951.png?t=1732593534.8700738
7,15,0.21572201,0.15297481,0,0.08273747157300083,0.016519931061773654,"[0.997855822565475, 0.0007319595622661134, 3.519642258842005e-05, 0.0013585068003781845, 1.8514649292360602e-05]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,08GbdALmEs,Learning Versatile Skills with Curriculum Masking,reinforcement learning;unsupervised pretraining;masked prediction;curriculum learning,5.25,3.25,Yao Tang;Zhihui Xie;Zichuan Lin;Deheng Ye;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;Tencent AI Lab;Tencent;John Hopcroft Center, Shanghai Jiao Tong University",Undergrad student;MS student;Researcher;Principal Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96950,,,https://openreview.net/forum?id=08GbdALmEs,/media/PosterPDFs/NeurIPS%202024/96950.png?t=1733319308.3295946
7,16,-0.17784788,-0.16018736,3,-0.13817844936362567,-0.24997137110223888,"[0.06999845164864164, 7.551041241019096e-06, 1.5533876265526087e-13, 0.689015604924987, 0.240978392384975]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,08nbMTxazb,Chicks4FreeID: A Benchmark Dataset for Chicken Re-Identification,animal re-identification;chicken re-identification;chicken dataset;re-identification dataset;benchmark dataset;closed-set re-identification;computer vision;chicken instance segmentation;poultry;livestock,4.75,4.0,Daria Kern;Tobias Schiele;Ulrich Klauck;Winfred Ingabire,Glasgow Caledonian University;Hochschule Aalen;Glasgow Caledonian University,PhD student;Full Professor;Lecturer,,,,,
7,17,0.12485067,-0.17534988,0,0.08273747157300083,0.016519931061773654,"[0.47642281855379887, 0.3569981919304699, 1.0960317431342064e-17, 0.1665719769100453, 7.012605685820763e-06]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,08oUnmtj8Q,FSEO: A Few-Shot Evolutionary Optimization Framework for Expensive Multi-Objective Optimization and Constrained Optimization,Expensive optimization;few-shot optimization;multi-objective optimization;constrained optimization;surrogate-assisted evolutionary optimization,4.5,3.5,Xunzhao Yu,,,,,,,
7,18,-0.045080878,-0.32160506,3,-0.13817844936362567,-0.24997137110223888,"[0.30670601900660605, 0.011195077453528043, 3.6320339860396204e-25, 0.6820943525394079, 4.551000457952088e-06]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,09RKw0vXjR,Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations,feature selection;sparse coding;dictionary learning;compressed sensing;iterative hard thresholding;pruning method,5.75,3.0,Yasutoshi Ida;Sekitoshi Kanai;Atsutoshi Kumagai;Tomoharu Iwata;Yasuhiro Fujiwara,NTT;NTT;NTT;NTT;NTT,Researcher;Researcher;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96949,,,https://openreview.net/forum?id=09RKw0vXjR,/media/PosterPDFs/NeurIPS%202024/96949.png?t=1733375377.8112724
7,19,-0.29219365,-0.1354431,4,-0.1996801020901614,0.0024864258082550324,"[0.0019914088013081436, 1.2409522759269451e-08, 8.823228896438187e-12, 0.11660970561932618, 0.8813988731610197]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,09nyBqSdUz,RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance,Consistent image generation;Diverse image generation;Improve temporal-consistency;Feature injection from multiple images,5.5,4.0,Jiaojiao Fan;Haotian Xue;Qinsheng Zhang;Yongxin Chen,Georgia Institute of Technology;Georgia Institute of Technology;Georgia Institute of Technology;NVIDIA,PhD student;PhD student;Associate Professor;Research Intern,https://neurips.cc/virtual/2024/poster/96948,,,https://openreview.net/forum?id=09nyBqSdUz,/media/PosterPDFs/NeurIPS%202024/96948.png?t=1731392354.7708242
7,20,0.22983314,0.005944166,0,0.08273747157300083,0.016519931061773654,"[0.710020321667947, 0.2714872839197501, 3.6782640708792393e-10, 0.018486196910866698, 6.1971336098439326e-06]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0AumdfLzpK,A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations,Visual Reinforcement Learning;Generalization,6.0,4.0,Wonil Song;Hyesong Choi;Kwanghoon Sohn;Dongbo Min,Yonsei Univ.;Ewha Womans University;Yonsei University;Ewha Womans University,PhD student;PhD student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96947,,,https://openreview.net/forum?id=0AumdfLzpK,/media/PosterPDFs/NeurIPS%202024/96947.png?t=1732451612.1247888
7,21,-0.2313607,0.15489271,4,-0.1996801020901614,0.0024864258082550324,"[0.00020887102635172932, 5.347402070335913e-14, 0.15994333549196457, 3.481344102756827e-05, 0.8398129800406028]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0AwMciNShl,"Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality",Human evaluation;text-to-video models,5.25,4.0,Tianle Zhang;Langtian Ma;Yuchen Yan;Yuchen Zhang;Yue Yang;Ziyao Guo;Wenqi Shao;Kai Wang;Yang You;Yu Qiao;Ping Luo;Kaipeng Zhang,University of Electronic Science and Technology of China;Southern University of Science and Technology;The University of Nottingham Ningbo China;University of Electronic Science and Technology of China;Xidian University;Shanghai AI Laboratory;National University of Singapore;National University of Singapore;Shanghai AI Laboratory;The University of Hong Kong;Shanghai Jiaotong University,Undergrad student;Undergrad student;Undergrad student;Undergrad student;MS student;Researcher;PhD student;Professor;Researcher;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96946,,,https://openreview.net/forum?id=0AwMciNShl,/media/PosterPDFs/NeurIPS%202024/96946.png?t=1729079669.652648
7,22,0.44196302,-0.22339565,1,0.392824477738228,-0.0839010650724529,"[1.3684056526959948e-06, 0.9999983745617591, 6.682990961320591e-29, 2.570325881181146e-07, 1.9365767985593456e-18]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0C3bLHwjsY,Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions,Online Matching;Competitive Analysis;Fairness Maximization,6.25,3.0,Will Ma;Pan Xu,Columbia University;New Jersey Institute of Technology,Assistant Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96945,,,https://openreview.net/forum?id=0C3bLHwjsY,/media/PosterPDFs/NeurIPS%202024/96945.png?t=1731641014.5806563
7,23,0.31953293,-0.23248373,1,0.392824477738228,-0.0839010650724529,"[0.00030681813967330053, 0.9996347018147024, 3.850719773891597e-26, 5.8480045526618014e-05, 9.763995599419658e-14]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0DE1dLMW2b,Quantum algorithm for large-scale market equilibrium computation,market equilibrium computation;quantum algorithm,6.0,2.75,Po-Wei Huang;Patrick Rebentrost,Centre for Quantum Technologies;National University of Singapore,Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96944,,,https://openreview.net/forum?id=0DE1dLMW2b,/media/PosterPDFs/NeurIPS%202024/96944.png?t=1731426989.5298698
7,24,0.0025802255,-0.08199731,0,0.08273747157300083,0.016519931061773654,"[0.6654694436725019, 0.001025924253845523, 4.4034712279991075e-11, 0.3083740284110222, 0.025130603618595752]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0EfUYVMrLv,Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment,non-stationary environments;continuous distribution shift;test-time adaptation;unlabeled data,6.666666666666667,4.0,Zhen-Yu Zhang;Zhiyu Xie;Huaxiu Yao;Masashi Sugiyama,"RIKEN;Stanford University;Department of Computer Science, University of North Carolina at Chapel Hill;The University of Tokyo",Postdoc;MS student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96943,,,https://openreview.net/forum?id=0EfUYVMrLv,/media/PosterPDFs/NeurIPS%202024/96943.png?t=1731687693.6296034
7,25,0.023439856,-0.079839304,0,0.08273747157300083,0.016519931061773654,"[0.7220251923488278, 0.001998367075945186, 3.1199799871030245e-11, 0.26372391380062704, 0.012252526743400318]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0G0VpMjKyV,Sketching for Distributed Deep Learning: A Sharper Analysis,sketching;distributed learning;federated learning;optimization,5.666666666666667,4.0,Mayank Shrivastava;Berivan Isik;Qiaobo Li;Sanmi Koyejo;Arindam Banerjee,"University of Illinois, Urbana Champaign;Stanford University;Department of Computer Science, University of Illinois at Urbana-Champaign;University of Illinois, Urbana Champaign;Google",MS student;PhD student;PhD student;Professor;Research Scientist,https://neurips.cc/virtual/2024/poster/96942,,,https://openreview.net/forum?id=0G0VpMjKyV,/media/PosterPDFs/NeurIPS%202024/96942.png?t=1733481266.9121125
7,26,-0.06371302,0.3954228,2,-0.11663928851106392,0.32384781611338126,"[0.00019376810381684998, 3.944851507460353e-18, 0.9998015319267463, 1.3293450094164217e-09, 4.698640091893453e-06]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,0G5OK5vmmg,WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts,Benchmark;Large Language Models;Classical Chinese Literature and Language Arts,6.25,2.75,Jiahuan Cao;Yang Liu;Yongxin Shi;Kai Ding;Lianwen Jin,South China University of Technology;South China University of Technology;South China University of Technology;INTSIG Information;South China University of Technology,MS student;MS student;PhD student;Researcher;Professor,https://neurips.cc/virtual/2024/poster/97880,,,,/media/PosterPDFs/NeurIPS%202024/97880.png?t=1730896668.2191207
7,27,-0.2963673,0.015343715,4,-0.1996801020901614,0.0024864258082550324,"[4.7201753626378036e-05, 1.6800465878216094e-12, 6.80989826837869e-06, 0.0004598005802570296, 0.9994861877661679]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0G8AXwtmy2,T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition,harmful dataset;harmful content detection;Vision Language Model,6.5,3.75,Chen Yeh;You-Ming Chang;Wei-Chen Chiu;Ning Yu,National Yang Ming Chiao Tung University;National Yang Ming Chiao Tung University;National Chiao Tung University,MS student;MS student;Associate Professor,https://neurips.cc/virtual/2024/poster/97879,,,,/media/PosterPDFs/NeurIPS%202024/97879.png?t=1730218737.4487233
7,28,0.08612508,0.3898904,2,-0.11663928851106392,0.32384781611338126,"[0.0991120213907297, 7.371576421553403e-13, 0.9008847738135101, 1.78176859768903e-07, 3.026618163492893e-06]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,0Gl5WxY6es,Grounding Multimodal Large Language Models in Actions,Embodied AI;Multimodal Large Language Models;Reinforcement Learning;Imitation Learning,6.0,3.6666666666666665,Andrew Szot;Bogdan Mazoure;Harsh Agrawal;R Devon Hjelm;Zsolt Kira;Alexander T Toshev,Georgia Institute of Technology;Apple;Apple;Apple;Georgia Institute of Technology;Apple,PhD student;Research Scientist;Researcher;Researcher;Assistant Professor;research scientist,https://neurips.cc/virtual/2024/poster/96941,,,https://openreview.net/forum?id=0Gl5WxY6es,
7,29,-0.20296153,0.2345368,2,-0.11663928851106392,0.32384781611338126,"[4.6481422132468444e-05, 3.370364021704146e-16, 0.9715978438123387, 5.587763841600711e-07, 0.02835511598914431]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,0Gmi8TkUC7,GenAI Arena: An Open Evaluation Platform for Generative Models,Evaluation;Benchmark;Platform;Generative Model,6.0,3.5,Dongfu Jiang;Max Ku;Tianle Li;Yuansheng Ni;Shizhuo Sun;Rongqi Fan;Wenhu Chen,Allen Institute for Artificial Intelligence;University of Waterloo;University of Waterloo;University of Toronto;NVIDIA;University of Waterloo,Intern;MS student;MS student;Undergrad student;Intern;Assistant Professor,https://neurips.cc/virtual/2024/poster/97878,,,,/media/PosterPDFs/NeurIPS%202024/97878.png?t=1730329031.3167162
7,30,-0.3021013,-0.23802479,3,-0.13817844936362567,-0.24997137110223888,"[0.00772190320224787, 4.5703219367924305e-07, 2.7123888865255974e-17, 0.9249469331933566, 0.06733070657220196]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,0HRRNEAQFp,A General Protocol to Probe Large Vision Models for 3D Physical Understanding,3D physical scene understanding; Representation probing protocol; Benchmark and evaluation,6.333333333333333,4.0,Guanqi Zhan;Chuanxia Zheng;Weidi Xie;Andrew Zisserman,University of Oxford;University of Oxford;Shanghai Jiaotong University,PhD student;Postdoc;Associate Professor,https://neurips.cc/virtual/2024/poster/96940,,,https://openreview.net/forum?id=0HRRNEAQFp,/media/PosterPDFs/NeurIPS%202024/96940.png?t=1731705235.0575316
7,31,0.40233114,0.06031101,1,0.392824477738228,-0.0839010650724529,"[0.006195868881241093, 0.9937589604294794, 3.3843212053857695e-12, 4.517066910942017e-05, 1.6785875601932463e-11]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0JSKjdePGq,When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL,reinforcement learning;continuous-time,6.75,3.25,Lenart Treven;Bhavya Sukhija;Yarden As;Florian Dorfler;Andreas Krause,"Swiss Federal Institute of Technology;ETHZ - ETH Zurich;Department of Computer Science, ETHZ - ETH Zurich;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96939,,,https://openreview.net/forum?id=0JSKjdePGq,/media/PosterPDFs/NeurIPS%202024/96939.png?t=1730197260.75527
7,32,-0.31179968,-0.050893012,4,-0.1996801020901614,0.0024864258082550324,"[9.84028341889941e-05, 3.142936239106777e-11, 2.673041453913015e-08, 0.0034426947855196828, 0.9964588756184476]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0KseSacluJ,CoFie: Learning Compact Neural Surface Representations with Coordinate Fields,Neural Surface Representation;Shape Auto-Decoding;Coordinate Field.,5.0,4.0,Hanwen Jiang;Haitao Yang;Georgios Pavlakos;Qixing Huang,University of Texas at Austin;The University of Texas at Austin;University of Texas at Austin;University of Texas at Austin,PhD student;PhD student;Assistant Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96938,,,https://openreview.net/forum?id=0KseSacluJ,
7,33,0.11298243,0.035079706,0,0.08273747157300083,0.016519931061773654,"[0.9662547257645113, 0.0014010151696911674, 1.91401605592997e-07, 0.03014798650994442, 0.0021960811542476835]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0KvYLaTBTE,Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference,Generative models;Reinforcement learning;Decision transformer,6.333333333333333,3.0,Deqian Kong;Dehong Xu;Minglu Zhao;Bo Pang;Jianwen Xie;Andrew Lizarraga;Yuhao Huang;Sirui Xie;Ying Nian Wu,"University of California, Los Angeles;Amazon;University of California, Los Angeles;University of California, Los Angeles;Xi'an Jiaotong University;University of California, Los Angeles;University of California, Los Angeles;UCLA",PhD student;Intern;PhD student;PhD student;PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96937,,,https://openreview.net/forum?id=0KvYLaTBTE,
7,34,-0.23456638,0.06657637,4,-0.1996801020901614,0.0024864258082550324,"[0.00025058649558013413, 3.739053354045772e-12, 0.000274058214188978, 0.0003141685592598418, 0.999161186727232]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0LXotew9Du,KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization,Quantization;KV Cache;LLM Inference;Compression;Long Context Length,6.25,3.25,Coleman Richard Charles Hooper;Sehoon Kim;Hiva Mohammadzadeh;Michael W. Mahoney;Sophia Shao;Kurt Keutzer;Amir Gholami,"University of California, Berkeley;University of California, Berkeley;University of California, Berkeley;University of California, Berkeley",PhD student;PhD student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96936,,,https://openreview.net/forum?id=0LXotew9Du,
7,35,0.11017645,-0.16371755,0,0.08273747157300083,0.016519931061773654,"[0.58061129281672, 0.20911141362390095, 8.830277473479237e-17, 0.21025356174864632, 2.3731810732622797e-05]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0Lb8vZT1DB,Reliable Learning of Halfspaces under Gaussian Marginals,reliable learning;agnostic learning;halfspace;proper leaning;statistical query,7.25,2.25,Ilias Diakonikolas;Lisheng Ren;Nikos Zarifis,"University of Wisconsin - Madison;University of Wisconsin - Madison;University of Wisconsin, Madison",Full Professor;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96935,,,https://openreview.net/forum?id=0Lb8vZT1DB,
7,36,0.1429859,0.059452157,0,0.08273747157300083,0.016519931061773654,"[0.981794273800027, 0.0017804252971878156, 5.601019018647867e-07, 0.01575138145569221, 0.0006733593451913478]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0LfgE6kvKZ,Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning,Federated Learning; Model Merging,5.0,3.6666666666666665,Minghui Chen;Meirui Jiang;Xin Zhang;Qi Dou;Zehua Wang;Xiaoxiao Li,"University of British Columbia;Meta Facebook;The Chinese University of Hong Kong;University of British Columbia;University of British Columbia;Department of Computer Science and Engineering, The Chinese University of Hong Kong",PhD student;Research Scientist;Assistant Professor;Researcher;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96934,,,https://openreview.net/forum?id=0LfgE6kvKZ,/media/PosterPDFs/NeurIPS%202024/96934.png?t=1731518093.5294044
7,37,-0.040502112,0.02318828,4,-0.1996801020901614,0.0024864258082550324,"[0.3901894219517197, 5.222478712636744e-06, 4.718366635438911e-06, 0.06554827985860688, 0.5442523573443254]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0Lr9HQijA1,Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations,Imprecise Label Learning,5.75,3.0,Hao Chen;Ankit Shah;Jindong Wang;Ran Tao;Yidong Wang;Xiang Li;Xing Xie;Masashi Sugiyama;Rita Singh;Bhiksha Raj,"Carnegie Mellon University;Accenture;Microsoft Research;Peking University;Microsoft Research Asia;The University of Tokyo;School of Computer Science, Carnegie Mellon University;Mohamed bin Zayed University of Artificial Intelligence",PhD student;Principal Researcher;Researcher;PhD student;Senior Principal Researcher;Full Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96933,,,https://openreview.net/forum?id=0Lr9HQijA1,/media/PosterPDFs/NeurIPS%202024/96933.png?t=1731704880.9846606
7,38,-0.06471333,0.08954511,4,-0.1996801020901614,0.0024864258082550324,"[0.1445020489712711, 6.541630016210184e-08, 0.0010945207790180318, 0.00914428159048478, 0.8452590832429259]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0MXzbAv8xy,GFT: Graph Foundation Model with Transferable Tree Vocabulary,Graph Foundation Model;Transferability;Computation Tree;Graph Neural Network,6.0,3.75,Zehong Wang;Zheyuan Zhang;Nitesh V Chawla;Chuxu Zhang;Yanfang Ye,University of Notre Dame;University of Notre Dame;University of Notre Dame;University of Notre Dame,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96932,,,https://openreview.net/forum?id=0MXzbAv8xy,
7,39,0.06407858,0.09707585,0,0.08273747157300083,0.016519931061773654,"[0.9626986813840767, 2.1092907279553763e-05, 0.00012356595074142218, 0.013184961665450719, 0.023971698092451508]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0NMzBwqaAJ,Not All Tokens Are What You Need for Pretraining,pre-training;next token prediction;data optimization;data selection,7.666666666666667,4.0,Zhenghao Lin;Zhibin Gou;Yeyun Gong;Xiao Liu;yelong shen;Ruochen Xu;Chen Lin;Yujiu Yang;Jian Jiao;Nan Duan;Weizhu Chen,Xiamen University;Microsoft;Microsoft Research Asia;Microsoft Research;Xiamen University;Tsinghua University;Microsoft;Microsoft Research Asia;Microsoft GenAI,MS student;Intern;Researcher;Researcher;Full Professor;Full Professor;Principal Researcher;Principal Researcher;Vice President,https://neurips.cc/virtual/2024/poster/96931,,,https://openreview.net/forum?id=0NMzBwqaAJ,/media/PosterPDFs/NeurIPS%202024/96931.png?t=1733724962.7310221
7,40,-0.021407472,0.09407413,0,0.08273747157300083,0.016519931061773654,"[0.4966171402985247, 7.004911238660446e-07, 0.0010549521286766844, 0.017099920927861417, 0.4852272861538132]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0NQzQVu9tY,DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors,representation learning;offline reinforcement learning;behavioral cloning;visual distractor,7.0,3.0,Joseph Ortiz;Antoine Dedieu;Wolfgang Lehrach;J Swaroop Guntupalli;Carter Wendelken;Ahmad Humayun;Sivaramakrishnan Swaminathan;Guangyao Zhou;Miguel Lazaro-Gredilla;Kevin Patrick Murphy,Google DeepMind;Google DeepMind;Google Deepmind;Google DeepMind;Google;Google DeepMind;Google DeepMind;Google DeepMind;Google Deepmind;Google,Researcher;Researcher;Researcher;Researcher;Researcher;Researcher;Research Engineer;Research Scientist;Research Scientist;Principal Researcher,https://neurips.cc/virtual/2024/poster/97877,,,,/media/PosterPDFs/NeurIPS%202024/97877.png?t=1733266397.4133346
7,41,-0.056248758,0.025906589,4,-0.1996801020901614,0.0024864258082550324,"[0.25516505985730886, 1.933927070686469e-06, 6.9573965329767656e-06, 0.049386205394204706, 0.6954398434248829]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0SMhqvgHST,EEVEE and GATE: Finding the right benchmarks and how to run them seamlessly,multi-modal;benchmarks;machine learning;model evaluation;benchmark frameworks,6.0,4.0,Antreas Antoniou;Eleni Triantafillou;Hugo Larochelle;Sebastien Montella;Fady Rezk;Kiyoon Kim;Linus Ericsson;Pavlos Vougiouklis;Justin Engelmann;Elliot J. Crowley;Srihari Humbarwadi;Yi Liu;Guang Yang;Jeff Z. Pan;Amos Storkey,"Google;Google;Huawei Technologies Ltd.;Samsung;Deargen;University of Edinburgh, University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh, University of Edinburgh;University of Edinburgh",Researcher;Research Scientist;Researcher;Intern;Researcher;Postdoc;Researcher;Assistant Professor;Researcher;Full Professor;Full Professor,,,,,
7,42,-0.15132618,0.02146309,4,-0.1996801020901614,0.0024864258082550324,"[0.008920957658117555, 6.019038677608955e-09, 5.833069488484626e-06, 0.0067505867110100965, 0.9843226165423451]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0SRJBtTNhX,IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors,Graph Machine Learning;Graph Data Augmentation;Graph Neural Networks,5.5,4.0,Shenghe Zheng;Hongzhi Wang;Xianglong Liu,Harbin Institute of Technology;Harbin Institute of Technology;Harbin Institute of Technology,MS student;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96930,,,https://openreview.net/forum?id=0SRJBtTNhX,/media/PosterPDFs/NeurIPS%202024/96930.png?t=1732617637.3891017
7,43,-0.18518934,0.0027779788,4,-0.1996801020901614,0.0024864258082550324,"[0.003215182434038318, 1.9401320585290848e-09, 1.3409070305155435e-06, 0.005575271421640915, 0.9912082032971581]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0T8xRFrScB,Benchmarking Counterfactual Image Generation,benchmark;causal inference;counterfactual image generation,7.25,3.75,Thomas Melistas;Nikos Spyrou;Nefeli Gkouti;Pedro Sanchez;Athanasios Vlontzos;Yannis Panagakis;Giorgos Papanastasiou;Sotirios A. Tsaftaris,"University of Athens;University of Athens;University of Athens;University of Edinburgh, University of Edinburgh;Spotify;Pfizer;University of Edinburgh",PhD student;PhD student;PhD student;PhD student;Researcher;Principal Researcher;Professor in machine learning and computer vision,https://neurips.cc/virtual/2024/poster/97876,,,,/media/PosterPDFs/NeurIPS%202024/97876.png?t=1731712408.6398222
7,44,0.5118622,-0.024860546,1,0.392824477738228,-0.0839010650724529,"[1.6440236538945388e-06, 0.9999982911810648, 9.338154987368034e-20, 6.479528146508285e-08, 9.32363570040344e-18]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0TUMAAb3of,Queueing Matching Bandits with Preference Feedback,Bandits;Queue;Preference Feedback,6.0,2.5,Jung-hun Kim;Min-hwan Oh,Seoul National University;Seoul National University,Assistant Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96929,,,https://openreview.net/forum?id=0TUMAAb3of,/media/PosterPDFs/NeurIPS%202024/96929.png?t=1733803835.532587
7,45,-0.0018669573,0.3644946,2,-0.11663928851106392,0.32384781611338126,"[0.004251207651366968, 5.783236314631092e-15, 0.9957290227703105, 4.570213986633546e-08, 1.972387617701418e-05]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,0VeSCjRDBy,Adversarial Moment-Matching Distillation of Large Language Models,Knowledge distillation;Large language models;Imitation learning;Moment-matching;Adversarial training,6.25,3.0,Chen Jia,,,https://neurips.cc/virtual/2024/poster/96928,,,https://openreview.net/forum?id=0VeSCjRDBy,/media/PosterPDFs/NeurIPS%202024/96928.png?t=1731660620.7591212
7,46,-0.24925767,0.015651966,4,-0.1996801020901614,0.0024864258082550324,"[0.0002527411865241112, 2.2560062452871147e-11, 5.037567639163248e-06, 0.0010354507648572715, 0.9987067704584195]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0WCFI2Qx85,ScaleKD: Strong Vision Transformers Could Be Excellent Teachers,knowledge distillation;model compression;training acceleration;vision transformer;convolutional neural network;multi-layer perception,6.25,4.5,Jiawei Fan;Chao Li;Xiaolong Liu;Anbang Yao,Intel Labs China;Intel;Intel,Research Intern;Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96927,,,https://openreview.net/forum?id=0WCFI2Qx85,/media/PosterPDFs/NeurIPS%202024/96927.png?t=1731695837.2500114
7,47,0.2804453,-0.1894261,1,0.392824477738228,-0.0839010650724529,"[0.0028521994221200058, 0.996646091583303, 2.497367963546126e-22, 0.0005017089666960949, 2.7880853133982553e-11]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0XKvW4ijxp,Learning-Augmented Algorithms with Explicit Predictors,online algorithms;learning-augmented algorithms;scheduling;caching,6.0,4.0,Marek Elias;Haim Kaplan;Yishay Mansour;Shay Moran,"Bocconi University;Technion, Technion;School of Computer Science, Tel Aviv University",Assistant Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96926,,,https://openreview.net/forum?id=0XKvW4ijxp,/media/PosterPDFs/NeurIPS%202024/96926.png?t=1733319671.0065775
7,48,0.37225774,-0.11562894,1,0.392824477738228,-0.0839010650724529,"[0.00020100121927084873, 0.9997807849011365, 1.8462032457000427e-20, 1.821387934603578e-05, 2.466887220177597e-13]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0XeNkkENuI,The Road Less Scheduled,Stochastic Optimization;Optimization;Convex Optimization;Learning Rates;Learning Rate Schedules,7.5,3.5,Aaron Defazio;Xingyu Alice Yang;Ahmed Khaled;Konstantin Mishchenko;Harsh Mehta;Ashok Cutkosky,Meta;Meta;Princeton University;Samsung;Google Research;Boston University,Research Scientist;Research Engineer;PhD student;Researcher;Software Engineer;Assistant Professor,https://neurips.cc/virtual/2024/poster/96925,,,https://openreview.net/forum?id=0XeNkkENuI,/media/PosterPDFs/NeurIPS%202024/96925.png?t=1730837481.9895687
7,49,0.1460578,0.21914145,0,0.08273747157300083,0.016519931061773654,"[0.9896613361678214, 1.6970866698401977e-06, 0.009784796507530155, 0.00034162335517007845, 0.00021054688280857395]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0ZZMUjZJYF,Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study,LLMs;Learning by Teaching;Reasoning;Mathematical Reasoning;Code Synthesis;Weak-to-Strong Generalization;In-Context Learning;Prompting;Knowledge Distillation;Education-Inspired,6.5,4.0,Xuefei Ning;Zifu Wang;Shiyao Li;Zinan Lin;Peiran Yao;Tianyu Fu;Matthew B. Blaschko;Guohao Dai;Huazhong Yang;Yu Wang,Tsinghua University;KU Leuven;Tsinghua University;Microsoft;Infinigence;Shanghai Jiaotong University;Tsinghua University;Tsinghua University;KU Leuven,Research Assistant Professor;PhD student;PhD student;Senior Researcher;Researcher;Associate Professor;Full Professor;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96924,,,https://openreview.net/forum?id=0ZZMUjZJYF,/media/PosterPDFs/NeurIPS%202024/96924.png?t=1732367562.4969194
7,50,0.07159563,-0.024327766,0,0.08273747157300083,0.016519931061773654,"[0.8901636503602329, 0.002257871709128611, 2.8184356173679406e-09, 0.10151459777048942, 0.006063877341713477]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0ZeONp33f0,Graph Neural Networks and Arithmetic Circuits,Machine Learning;Graph Neural Networks;Arithmetic Circuits;Computational Complexity,6.5,3.25,Timon Barlag;Vivian Holzapfel;Laura Strieker;Jonni Virtema;Heribert Vollmer,Universität Hannover;Leibniz Universität Hannover;Leibniz Universität Hannover;University of Sheffield;Leibniz Universität Hannover,PhD student;Undergrad student;PhD student;Lecturer;Full Professor,https://neurips.cc/virtual/2024/poster/96923,,,https://openreview.net/forum?id=0ZeONp33f0,/media/PosterPDFs/NeurIPS%202024/96923.png?t=1732106485.9402945
7,51,-0.078428976,-0.18954016,3,-0.13817844936362567,-0.24997137110223888,"[0.2575805633232632, 0.000560813346223699, 3.633884205135837e-16, 0.7343559246141715, 0.007502698716341357]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,0aN7VWwp4g,Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting,Precipitation Nowcasting;Video Prediction;Fourier Analysis;Loss Function,6.0,4.0,Chiu-Wai Yan;Shi Quan Foo;Van-Hoan Trinh;Dit-Yan Yeung;Ka-Hing Wong;Wai-Kin Wong,Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology,Chair Professor;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96922,,,https://openreview.net/forum?id=0aN7VWwp4g,/media/PosterPDFs/NeurIPS%202024/96922.png?t=1731480203.951872
7,52,-0.23586994,0.37846398,2,-0.11663928851106392,0.32384781611338126,"[8.052247824649297e-08, 3.056600068383197e-23, 0.9999945617750502, 1.3639798648410129e-11, 5.357688831735831e-06]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,0bFXbEMz8e,FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions,generative models;material generation;chemistry;flow matching;large language models,6.0,4.333333333333333,Anuroop Sriram;Benjamin Kurt Miller;Ricky T. Q. Chen;Brandon M Wood,"Meta Facebook;University of Amsterdam;FAIR at Meta;FAIR Labs, Meta AI",Principal Researcher;PhD student;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96921,,,https://openreview.net/forum?id=0bFXbEMz8e,/media/PosterPDFs/NeurIPS%202024/96921.png?t=1730973273.143089
7,53,-0.15925287,-0.015642455,4,-0.1996801020901614,0.0024864258082550324,"[0.011292512679665618, 2.4816596300210933e-08, 2.7271114681791247e-07, 0.017453895045218118, 0.9712532947473733]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0bINeW40u4,Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning,Medical Multi-modal Alignment;Eye-gaze;Radiology,6.25,3.5,Chong Ma;Hanqi Jiang;Wenting Chen;Yiwei Li;Zihao Wu;Xiaowei Yu;Zhengliang Liu;Lei Guo;Dajiang Zhu;Tuo Zhang;Dinggang Shen;Tianming Liu;Xiang Li,"Northwest Polytechnical University Xi'an;Beijing Jiaotong University;City University of Hong Kong;University of Georgia;University of Georgia;University of Texas at Arlington, University of Texas at Arlington;University of Georgia;University of Texas at Arlington;Northwestern Polytechnical University;ShanghaiTech University;University of Georgia;Massachusetts General Hospital, Harvard University",PhD student;Undergrad student;PhD student;PhD student;PhD student;PhD student;PhD student;Assistant Professor;Associate Professor;Full Professor;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96920,,,https://openreview.net/forum?id=0bINeW40u4,
7,54,0.38273144,-0.19184409,1,0.392824477738228,-0.0839010650724529,"[3.2541023787730296e-05, 0.9999623816052319, 2.6932950045625356e-25, 5.077370977997786e-06, 2.5088659963231355e-15]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0cSQ1Sg7db,Generalization of Hamiltonian algorithms,Generalization;stochastic algorithms;concentration inequalities;PAC-Bayes,6.5,3.0,Andreas Maurer,,,https://neurips.cc/virtual/2024/poster/96919,,,https://openreview.net/forum?id=0cSQ1Sg7db,
7,55,-0.029614072,-0.05991212,0,0.08273747157300083,0.016519931061773654,"[0.5749642852051802, 0.00017701880579497535, 1.2497073616097276e-09, 0.2922685251882795, 0.13259016955103808]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0cgDDa4OFr,Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation,source distribution estimation;maximum entropy;Sliced-Wasserstein distance;empirical Bayes;simulation-based inference,5.8,2.8,Julius Vetter;Guy Moss;Cornelius Schröder;Richard Gao;Jakob H. Macke,Eberhard-Karls-Universität Tübingen;Eberhard-Karls-Universität Tübingen;University Tübingen;Eberhard-Karls-Universität Tübingen,PhD student;PhD student;Postdoc;Postdoc,https://neurips.cc/virtual/2024/poster/96918,,,https://openreview.net/forum?id=0cgDDa4OFr,/media/PosterPDFs/NeurIPS%202024/96918.png?t=1733318904.6928847
7,56,-0.041920777,-0.1336057,3,-0.13817844936362567,-0.24997137110223888,"[0.4327247638910251, 0.0007097555999891707, 2.738859343263438e-13, 0.5438861494120776, 0.022679331096634146]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,0d50Il6enG,Non-parametric classification via expand-and-sparsify representation,non-parametric regression;non-parametric classification;expand-and-sparsify representation;universal consistency;minimax-optimal convergence rate,6.0,3.0,Kaushik Sinha,Wichita State University,Associate Professor,https://neurips.cc/virtual/2024/poster/96917,,,https://openreview.net/forum?id=0d50Il6enG,/media/PosterPDFs/NeurIPS%202024/96917.png?t=1731697679.5420048
7,57,-0.05421332,-0.22073112,3,-0.13817844936362567,-0.24997137110223888,"[0.2933602774523992, 0.0021694549724746233, 2.4464827745083133e-18, 0.7035283414605852, 0.0009419261145410403]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,0dtA21q83C,DeNetDM: Debiasing by Network Depth Modulation,Trustworthy Machine Learning;Debiasing;Robustness,6.0,3.5,Silpa Vadakkeeveetil Sreelatha;Adarsh Kappiyath;Abhra Chaudhuri;Anjan Dutta,University of Surrey;University of Exeter;University of Surrey,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96916,,,https://openreview.net/forum?id=0dtA21q83C,/media/PosterPDFs/NeurIPS%202024/96916.png?t=1733689557.490417
7,58,-0.19589648,0.09422963,4,-0.1996801020901614,0.0024864258082550324,"[0.000927728972085411, 9.973172039786649e-12, 0.001904447428487261, 0.0003464565539489047, 0.9968213670355053]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0e5uOaJxo1,Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure,Graph Neural Network;Protein Sequence;Structure,5.0,3.3333333333333335,Bozhen Hu;Cheng Tan;Jun Xia;Yue Liu;Lirong Wu;Jiangbin Zheng;Yongjie Xu;Yufei Huang;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University, China;National University of Singapore;Westlake University;Westlake University;Westlake University;Zhejiang University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96915,,,https://openreview.net/forum?id=0e5uOaJxo1,/media/PosterPDFs/NeurIPS%202024/96915.png?t=1730385968.8958924
7,59,0.09615892,0.18102637,0,0.08273747157300083,0.016519931061773654,"[0.9865953373444144, 1.5815402947572852e-06, 0.008386442010206224, 0.0013892940258209774, 0.0036273450792635325]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0feJEykDRx,Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models,spatial-temporal data mining;location-based service;check-in sequence;large language model,5.75,4.0,Letian Gong;Yan Lin;Xinyue Zhang;Yiwen Lu;Xuedi Han;Yichen Liu;Shengnan Guo;Youfang Lin;Huaiyu Wan,Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University,PhD student;PhD student;Undergrad student;Undergrad student;MS student;Associate Professor;Full Professor;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96914,,,https://openreview.net/forum?id=0feJEykDRx,/media/PosterPDFs/NeurIPS%202024/96914.png?t=1731289337.5941467
7,60,-0.013711061,-0.07216554,0,0.08273747157300083,0.016519931061773654,"[0.6304074644140936, 0.0004480766305007929, 2.1170743588368564e-10, 0.31097527892560073, 0.058169179818097536]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0jld45XGgJ,Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?,neural collapse;deep neural collapse;unconstrained features model;deep unconstrained features model;low-rank bias,6.5,3.75,Peter Súkeník;Christoph H. Lampert;Marco Mondelli,Institute of Science and Technology;Institute of Science and Technology Austria;Institute of Science and Technology Austria,PhD student;Assistant Professor;Professor,https://neurips.cc/virtual/2024/poster/96913,,,https://openreview.net/forum?id=0jld45XGgJ,
7,61,0.49365819,-0.019841706,1,0.392824477738228,-0.0839010650724529,"[4.931191687279137e-06, 0.9999948993803304, 6.110584963650168e-19, 1.6942798224255663e-07, 7.622137180661035e-17]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0l9yGPTHAU,Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms,Robust Markov decision process;norm;sample complexity;strong duality,6.5,3.0,Pierre Clavier;Laixi Shi;Erwan Le Pennec;Eric Mazumdar;Adam Wierman;Matthieu Geist,"École Polytechnique;California Institute of Technology;Ecole polytechnique;Deparment of Computing + Mathematical Sciences, California Institute of Technology;California Institute of Technology;Google",PhD student;Postdoc;Full Professor;Assistant Professor;Professor;Researcher,https://neurips.cc/virtual/2024/poster/96912,,,https://openreview.net/forum?id=0l9yGPTHAU,
7,62,-0.096782275,0.2680031,2,-0.11663928851106392,0.32384781611338126,"[0.0011502249470720638, 2.4340514202527327e-14, 0.9938894240753885, 1.035690150350487e-06, 0.004959315287364833]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,0lBx844upd,ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models,network pruning;unstructured pruning;large language model;ADMM;pre-conditioned conjugate gradient;optimization,5.333333333333333,3.0,Xiang Meng;Kayhan Behdin;Haoyue Wang;Rahul Mazumder,Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology,PhD student;PhD student;PhD student;Associate Professor,https://neurips.cc/virtual/2024/poster/96911,,,https://openreview.net/forum?id=0lBx844upd,/media/PosterPDFs/NeurIPS%202024/96911.png?t=1731079283.0533488
7,63,-0.07022652,-0.30347943,3,-0.13817844936362567,-0.24997137110223888,"[0.24084100864227345, 0.003900383188630795, 1.1347152792747367e-23, 0.7552339778767069, 2.4630292388968963e-05]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,0lau89u4oE,Accelerating Non-Maximum Suppression: A Graph Theory Perspective,non-maximum suppression;object detection;graph theory,5.5,3.25,King-Siong Si;Lu Sun;Weizhan Zhang;Tieliang Gong;Jiahao Wang;Jiang Liu;Hao Sun,Xi'an Jiaotong University;Xi'an Jiaotong University;North China University of Technology;China Telecom Corporation Ltd. Data&AI Technology Company,MS student;MS student;MS student;Researcher,https://neurips.cc/virtual/2024/poster/96910,,,https://openreview.net/forum?id=0lau89u4oE,/media/PosterPDFs/NeurIPS%202024/96910.png?t=1733315333.5240822
7,64,-0.08510746,-0.26066056,3,-0.13817844936362567,-0.24997137110223888,"[0.20629212830192056, 0.001332757012407326, 1.2458876931465495e-20, 0.7920424054941012, 0.0003327091915708632]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,0m19blQT6y,BitsFusion: 1.99 bits Weight Quantization of Diffusion Model,Diffusion;Quantization;Stable Diffusion;Low bit,5.75,4.5,Yang Sui;Yanyu Li;Anil Kag;Yerlan Idelbayev;Junli Cao;Ju Hu;Dhritiman Sagar;Bo Yuan;Sergey Tulyakov;Jian Ren,Rutgers University;Northeastern University;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Rutgers University;Snap Inc.;Snap Inc.,PhD student;PhD student;Researcher;Researcher;Researcher;Researcher;Researcher;Assistant Professor;Director of Research;Research Scientist,https://neurips.cc/virtual/2024/poster/96909,,,https://openreview.net/forum?id=0m19blQT6y,/media/PosterPDFs/NeurIPS%202024/96909.png?t=1729915675.3170154
7,65,-0.00251228,0.3769304,2,-0.11663928851106392,0.32384781611338126,"[0.003422837570199646, 2.026154349371771e-15, 0.9965666115998552, 2.333776871427474e-08, 1.0527492174639012e-05]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,0mRouJElbZ,ProgressGym: Alignment with a Millennium of Moral Progress,Progress Alignment;AI Alignment;Large Language Models,7.666666666666667,2.6666666666666665,Tianyi Qiu;Yang Zhang;Xuchuan Huang;Jasmine Xinze Li;Jiaming Ji;Yaodong Yang,"University of California, Berkeley;Peking University;Peking University;Peking University;Peking University;Peking University",Intern;Undergrad student;Undergrad student;Intern;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/97875,,,,/media/PosterPDFs/NeurIPS%202024/97875.png?t=1731742041.9348912
7,66,0.42614552,0.08994585,1,0.392824477738228,-0.0839010650724529,"[0.005383412943542223, 0.9945945457555802, 1.3438842704355586e-11, 2.204128324563471e-05, 4.193192611372208e-12]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0nSY8NiILP,Tight Bounds for Learning RUMs from Small Slates,discrete choice;random utility model;approximation theory,6.0,2.75,Flavio Chierichetti;Mirko Giacchini;Ravi Kumar;Alessandro Panconesi;Andrew Tomkins,Sapienza University of Rome;Sapienza University of Rome;Google;Sapienza University of Rome;Google,Full Professor;PhD student;Research Scientist;Full Professor;Researcher,https://neurips.cc/virtual/2024/poster/96908,,,https://openreview.net/forum?id=0nSY8NiILP,/media/PosterPDFs/NeurIPS%202024/96908.png?t=1732698791.0319488
7,67,0.25132486,-0.20319358,1,0.392824477738228,-0.0839010650724529,"[0.007442037520883436, 0.991028524064599, 2.031154920384824e-22, 0.0015294382513385335, 1.6317912698104538e-10]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0nzKznCjFG,Private and Personalized Frequency Estimation in a Federated Setting,federated learning;personalization;privacy,5.75,3.0,Amrith Setlur;Vitaly Feldman;Kunal Talwar,Carnegie Mellon University;Apple AI Research;Apple,PhD student;Research Scientist;Research Scientist,https://neurips.cc/virtual/2024/poster/96907,,,https://openreview.net/forum?id=0nzKznCjFG,
7,68,-0.18157998,0.03947093,4,-0.1996801020901614,0.0024864258082550324,"[0.0023171089465769523, 3.649177327995271e-10, 2.6209378158497266e-05, 0.002027488154936588, 0.9956291931554102]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0o7Rd5jngV,Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling,Transformer;expressive power;theoretical insights,6.333333333333333,3.0,Mingze Wang;Weinan E,Peking University;Peking University,PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96906,,,https://openreview.net/forum?id=0o7Rd5jngV,
7,69,-0.12251995,-0.049827244,4,-0.1996801020901614,0.0024864258082550324,"[0.07456818197181474, 1.3084829130936634e-06, 1.2684095951233261e-08, 0.10893710755437765, 0.8164933893067984]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0o9E8AsFgW,DarkSAM: Fooling Segment Anything Model to Segment Nothing,Segment Anything Model;Adversarial Example,6.333333333333333,4.0,Ziqi Zhou;Yufei Song;Minghui Li;Shengshan Hu;Xianlong Wang;Leo Yu Zhang;Dezhong Yao;Hai Jin,Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Griffith University;Huazhong University of Science and Technology;Huazhong University of Science and Technology,PhD student;PhD student;Assistant Professor;Associate Professor;PhD student;Researcher;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96905,,,https://openreview.net/forum?id=0o9E8AsFgW,
7,70,-0.18423451,0.25213403,2,-0.11663928851106392,0.32384781611338126,"[4.84649007405206e-05, 2.097311714477387e-16, 0.9894803303666211, 2.550021360271578e-07, 0.010470949730502157]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,0oUutV92YF,ProtGO: Function-Guided Protein Modeling for Unified Representation Learning,Teacher-student;Knowledge Distillation;Protein Function,5.666666666666667,3.6666666666666665,Bozhen Hu;Cheng Tan;Yongjie Xu;Zhangyang Gao;Jun Xia;Lirong Wu;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University;Westlake University, China;Westlake University, China;Westlake University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96904,,,https://openreview.net/forum?id=0oUutV92YF,/media/PosterPDFs/NeurIPS%202024/96904.png?t=1730386167.5899446
7,71,-0.04843812,0.4040603,2,-0.11663928851106392,0.32384781611338126,"[0.0003479597877514892, 6.622239815256187e-18, 0.999648982055173, 1.415750750598314e-09, 3.056741324727403e-06]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,0og7nmvDbe,Confidence Regulation Neurons in Language Models,LLMs;Interpretability;Mechanistic Interpretability,7.0,3.75,Alessandro Stolfo;Ben Peng Wu;Wes Gurnee;Yonatan Belinkov;Xingyi Song;Mrinmaya Sachan;Neel Nanda,"ETHZ - ETH Zurich;University of Sheffield;Massachusetts Institute of Technology;Technion, Technion;University of Sheffield;Google DeepMind;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Assistant Professor;Lecturer;Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96903,,,https://openreview.net/forum?id=0og7nmvDbe,
7,72,0.25011468,-0.18353273,1,0.392824477738228,-0.0839010650724529,"[0.010653893147108582, 0.9873467639754673, 3.900506110920831e-21, 0.001999342373480191, 5.039438604228684e-10]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0qb8KoPsej,Accelerating Matroid Optimization through Fast Imprecise Oracles,matroid optimization;weak-strong models;learning-augmented algorithms;algorithms with predictions;query minimization;robustness,5.5,2.75,Franziska Eberle;Felix Hommelsheim;Alexander Lindermayr;Zhenwei Liu;Nicole Megow;Jens Schlöter,Technische Universität Berlin;Universität Bremen;Universität Bremen;Universität Bremen;Universität Bremen,Postdoc;Postdoc;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96902,,,https://openreview.net/forum?id=0qb8KoPsej,
7,73,0.24778247,-0.18444899,1,0.392824477738228,-0.0839010650724529,"[0.011502562067018154, 0.9863098271755035, 3.945953629427462e-21, 0.0021876101725967585, 5.84881288269313e-10]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0rl5vWOzRU,Score-Optimal Diffusion Schedules,Diffusion model;adaptive schedule;Annealed Langevin,6.0,3.0,Christopher Williams;Andrew Campbell;Arnaud Doucet;Saifuddin Syed,University of Oxford;University of Oxford;University of Oxford;University of Oxford,PhD student;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96901,,,https://openreview.net/forum?id=0rl5vWOzRU,
7,74,-0.17648138,-0.41862112,3,-0.13817844936362567,-0.24997137110223888,"[0.11123450516263873, 0.0004179148809573286, 2.4862854738312814e-31, 0.8883472387610639, 3.4119533997067556e-07]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,0sJBW05a2W,3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration,Point Cloud Registration;Focus and Matching,5.666666666666667,4.333333333333333,Liyuan Zhang;Le Hui;qi liu;Bo Li;Yuchao Dai,Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwestern Polytechnical University Xi'an;Northwestern Polytechnical University,MS student;Associate Professor;Researcher;Associate Professor;Professor,https://neurips.cc/virtual/2024/poster/96900,,,https://openreview.net/forum?id=0sJBW05a2W,/media/PosterPDFs/NeurIPS%202024/96900.png?t=1731333373.8074756
7,75,-0.16704087,-0.3598848,3,-0.13817844936362567,-0.24997137110223888,"[0.0901386974088838, 0.0002942151386212506, 6.372532132985102e-27, 0.9095568576743461, 1.022977814874618e-05]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,0sycTGl4In,4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization,Dynamic Novel View Synthesis;4D Gaussian splatting;Sparse reconstruction;in-the-wild,5.333333333333333,4.666666666666667,Mijeong Kim;Jongwoo Lim;Bohyung Han,Seoul National University;Seoul National University,Full Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96899,,,https://openreview.net/forum?id=0sycTGl4In,/media/PosterPDFs/NeurIPS%202024/96899.png?t=1733712090.5881364
7,76,0.61073065,0.018717432,1,0.392824477738228,-0.0839010650724529,"[2.193951756722092e-08, 0.9999999773392149, 8.825736816334846e-21, 7.212676880058042e-10, 8.802661669990618e-22]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,0uGlKYS7a2,Maximizing utility in multi-agent environments by anticipating the behavior of other learners,Game Theory; no regret; learning theory;,5.5,3.25,Angelos Assos;Yuval Dagan;Constantinos Costis Daskalakis,Massachusetts Institute of Technology;Massachusetts Institute of Technology,MS student;Full Professor,https://neurips.cc/virtual/2024/poster/96898,,,https://openreview.net/forum?id=0uGlKYS7a2,/media/PosterPDFs/NeurIPS%202024/96898.png?t=1731753379.9098587
7,77,-0.07488669,0.3827278,2,-0.11663928851106392,0.32384781611338126,"[0.00013895592484013656, 4.583379635477692e-18, 0.9998521975814301, 1.7830070474728283e-09, 8.844710722653846e-06]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,0uXtFk5KNJ,BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models,block coordinate descent;large language models,5.25,3.75,Qijun Luo;Hengxu Yu;Xiao Li,"The Chinese University of Hong Kong, Shenzhen;The Chinese University of Hong Kong, Shenzhen;Chinese University of Hong Kong Shen Zhen",PhD student;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96897,,,https://openreview.net/forum?id=0uXtFk5KNJ,/media/PosterPDFs/NeurIPS%202024/96897.png?t=1733743857.9232197
7,78,0.022653038,0.24370801,2,-0.11663928851106392,0.32384781611338126,"[0.27920988973840544, 1.2017621696482288e-09, 0.7097794535004124, 0.00013076002139830677, 0.010879895538021617]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,0zFVhMBZHJ,Mixture of Tokens: Continuous MoE through Cross-Example Aggregation,LLM;Mixture of Experts;MoE;conditional computation;fully-differentiable;language modeling,6.0,3.6666666666666665,Szymon Antoniak;Michał Krutul;Maciej Pióro;Jakub Krajewski;Jan Ludziejewski;Kamil Ciebiera;Krystian Król;Tomasz Odrzygóźdź;Marek Cygan;Sebastian Jaszczur,IDEAS NCBR Sp.;IDEAS NCBR Sp.;University of Warsaw;University of Warsaw;IDEAS NCBR Sp.;University of Warsaw;IDEAS NCBR;Nomagic;University of Warsaw,PhD student;Researcher;PhD student;PhD student;Intern;MS student;Postdoc;Founder / CTO;PhD student,https://neurips.cc/virtual/2024/poster/96896,,,https://openreview.net/forum?id=0zFVhMBZHJ,/media/PosterPDFs/NeurIPS%202024/96896.png?t=1730308223.324062
7,79,0.24368975,0.18879418,0,0.08273747157300083,0.016519931061773654,"[0.9989354099479703, 0.0004799001266591713, 0.00010047262724423821, 0.0004810402957643636, 3.1770023617916355e-06]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,0zWzJj6lO3,Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents,cooperative AI;AI safety;LLM agents;cognitive science;language model evaluation;dynamic evaluation;alignment;agency;evolving benchmarks;multi-agent interactions,5.75,3.5,Giorgio Piatti;Zhijing Jin;Max Kleiman-Weiner;Bernhard Schölkopf;Mrinmaya Sachan;Rada Mihalcea,Common Sense Machines;University of Michigan;Swiss Federal Institute of Technology,Principal Researcher;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96895,,,https://openreview.net/forum?id=0zWzJj6lO3,
7,80,-0.16938657,-0.05973538,4,-0.1996801020901614,0.0024864258082550324,"[0.017974897301261776, 1.3848195585357668e-07, 5.95448786658887e-09, 0.05935477877800371, 0.9226701794842909]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,0zfUiSX5si,AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases,De Novo Peptide sequencing;Proteomics;Mass Spectrum,5.333333333333333,3.0,Jun Xia;Shaorong Chen;Jingbo Zhou;Xiaojun Shan;Wenjie Du;Zhangyang Gao;Cheng Tan;Bozhen Hu;Jiangbin Zheng;Stan Z. Li,"Westlake University, China;Westlake University;Jilin University;University of Electronic Science and Technology of China;University of Science and Technology of China;Westlake University, China;Zhejiang University & Westlake University;Westlake University;Westlake University;Westlake University",PhD student;PhD student;Undergrad student;Undergrad student;Assistant Professor;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96894,,,https://openreview.net/forum?id=0zfUiSX5si,
7,81,-0.25151917,-0.28693447,3,-0.13817844936362567,-0.24997137110223888,"[0.01984853610760777, 6.1061321064342036e-06, 5.097374550848388e-21, 0.9774332017947234, 0.0027121559655624923]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,105ZuvpdyW,SegVol: Universal and Interactive Volumetric Medical Image Segmentation,Volumetric Medical Image Segmentation;3D Segmentation Foundation Model;Universal and Interactive 3D Segmentation,7.666666666666667,4.333333333333333,Yuxin Du;Fan BAI;Tiejun Huang;Bo Zhao,Beijing Academy of Artificial Intelligence;The Chinese University of Hong Kong;Peking University;BAAI,Intern;PhD student;Full Professor;Principal Researcher,https://neurips.cc/virtual/2024/poster/96893,,,https://openreview.net/forum?id=105ZuvpdyW,/media/PosterPDFs/NeurIPS%202024/96893.png?t=1731410503.871179
7,82,0.04577409,-0.24324691,0,0.08273747157300083,0.016519931061773654,"[0.48748037650881554, 0.08766269499701479, 8.404850534783351e-21, 0.4248450053501377, 1.1923144031887085e-05]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,1067784F6e,Data Distribution Valuation,Data distribution valuation;Huber model;Maximum mean discrepancy,6.333333333333333,4.333333333333333,Xinyi Xu;Shuaiqi Wang;Chuan-Sheng Foo;Bryan Kian Hsiang Low;Giulia Fanti,"National University of Singapore;Carnegie Mellon University;Institute for Infocomm Research, A*STAR;National University of Singapore;Carnegie Mellon University",PhD student;PhD student;Principal Scientist;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96892,,,https://openreview.net/forum?id=1067784F6e,/media/PosterPDFs/NeurIPS%202024/96892.png?t=1731176029.7581189
7,83,-0.22563006,-0.049784996,4,-0.1996801020901614,0.0024864258082550324,"[0.0019491328935084503, 3.1120632745318223e-09, 1.7270809834746253e-08, 0.014066232062228009, 0.9839846146613904]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,12A1RT1L87,Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?,Dataset Condensation;Dataset Distillation,5.666666666666667,3.6666666666666665,Lingao Xiao;Yang He,"School of Computer Science and  Engineering, Nanyang Technological University;Institute of High Performance Computing, Singapore, A*STAR",Undergrad student;Researcher,https://neurips.cc/virtual/2024/poster/96891,,,https://openreview.net/forum?id=12A1RT1L87,/media/PosterPDFs/NeurIPS%202024/96891.png?t=1731138766.8349779
7,84,-0.20074943,0.040258985,4,-0.1996801020901614,0.0024864258082550324,"[0.0011166030597585576, 1.0827053150053167e-10, 2.957715361415569e-05, 0.001308577947381102, 0.9975452417309756]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,135eKqDoRR,Bayesian-guided Label Mapping for Visual Reprogramming,visual reprogramming;adversarial reprogramming;output label mapping;Bayesian probability,7.25,4.0,Chengyi Cai;Zesheng Ye;Lei Feng;Jianzhong Qi;Feng Liu,University of Melbourne;Singapore University of Technology and Design;University of Melbourne;University of Melbourne,PhD student;Assistant Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96890,,,https://openreview.net/forum?id=135eKqDoRR,
7,85,-0.1496939,0.30529067,2,-0.11663928851106392,0.32384781611338126,"[2.9958973793770115e-05, 1.416865412564876e-17, 0.999466169856422, 1.7050784286615815e-08, 0.0005038541189999277]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,14hLJr6kZ3,Enhancing Domain Adaptation through Prompt Gradient Alignment,transfer learning; domain adaptation; prompt-tuning,6.25,3.25,Hoang Phan;Tung Lam Tran;Quyen Tran;Trung Le,VinAi Research;VinAI Research;Monash University;New York University,Research resident;Research Resident;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96889,,,https://openreview.net/forum?id=14hLJr6kZ3,/media/PosterPDFs/NeurIPS%202024/96889.png?t=1732036918.0147438
7,86,0.2630342,0.051892787,0,0.08273747157300083,0.016519931061773654,"[0.7476555346908657, 0.24467405593458866, 7.1875017551433234e-09, 0.007668514120823753, 1.888066220152409e-06]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,15460JjocO,Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners,multi-agent;reinforcement learning;robustness;diversity;specialization,7.0,3.6666666666666665,Rujikorn Charakorn;Poramate Manoonpong;Nat Dilokthanakul,Sakana AI;Vidyasirimedhi Institute of Science and Technology;King Mongkut's Institute of Technology Ladkrabang,Intern;Full Professor;Lecturer,https://neurips.cc/virtual/2024/poster/96888,,,https://openreview.net/forum?id=15460JjocO,/media/PosterPDFs/NeurIPS%202024/96888.png?t=1731395258.7214391
7,87,0.61719507,-0.024593957,1,0.392824477738228,-0.0839010650724529,"[4.715813724115855e-09, 0.9999999949632261, 4.8525399613872025e-23, 3.209601425157658e-10, 9.722573014247546e-23]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,15Jm9v7wCo,No-Regret Learning for Fair Multi-Agent Social Welfare Optimization,Online Learning;Nash Social Welfare,5.666666666666667,3.3333333333333335,Mengxiao Zhang;Ramiro Deo-Campo Vuong;Haipeng Luo,University of Southern California;University of Southern California,Undergrad student;Associate Professor,https://neurips.cc/virtual/2024/poster/96887,,,https://openreview.net/forum?id=15Jm9v7wCo,
7,88,-0.14552048,-0.15470643,3,-0.13817844936362567,-0.24997137110223888,"[0.12325610751711345, 2.4028021806201865e-05, 1.776602958035812e-13, 0.7164124225157952, 0.1603074419451074]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,15PS30UOUp,Kuro Siwo: 33 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping,Synthetic Aperture Radar;SAR;Deep Learning;Remote Sensing;Floods;dataset,6.75,3.75,Nikolaos Ioannis Bountos;Maria Sdraka;Angelos Zavras;Andreas Karavias;Ilektra Karasante;Themistocles Herekakis;Angeliki Thanasou;Dimitrios Michail;Ioannis Papoutsis,National Observatory of Athens;National Observatory of Athens;Harokopio University;The Centre for Research & Technology;National Observatory of Athens ;National Observatoty of Athens;National Observatory of Athens;Harokopio University;National Technical University of Athens,PhD student;Researcher;PhD student;Researcher;Researcher;Researcher;Researcher;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97874,,,,
7,89,0.004352061,-0.07103703,0,0.08273747157300083,0.016519931061773654,"[0.6907829426489185, 0.0008215008099805614, 1.4547743306160038e-10, 0.2769524174730396, 0.03144313892258393]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,164QnJsYjF,Dense Associative Memory Through the Lens of Random Features,Associative Memory;Kernels;Random Features;Hopfield Network,6.0,3.0,Benjamin Hoover;Duen Horng Chau;Hendrik Strobelt;Parikshit Ram;Dmitry Krotov,International Business Machines;International Business Machines;International Business Machines;Massachusetts Institute of Technology;Georgia Institute of Technology,AI Research Engineer;Principal Researcher;Principal Researcher;Researcher;Full Professor,https://neurips.cc/virtual/2024/poster/96886,,,https://openreview.net/forum?id=164QnJsYjF,/media/PosterPDFs/NeurIPS%202024/96886.png?t=1733846086.053208
7,90,-0.31772932,0.41427824,2,-0.11663928851106392,0.32384781611338126,"[7.237372158981393e-10, 2.9581183290232313e-27, 0.9999996516996006, 1.39146257424301e-13, 3.475765230999355e-07]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,168NLzTpw8,Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation,Vision-Language;Region-Level Understanding;Multimodal Large Language Model,5.75,3.75,Yaoyuan Liang;Zhuojun Cai;Jian Xu;Guanbo Huang;Yiran Wang;Xiao Liang;Jiahao Liu;Ziran Li;Jingang Wang;Shao-Lun Huang,"Tsinghua Shenzhen International Graduate School, Tsinghua University;Microsoft;University of Electronic Science and Technology of China;Tsinghua University;Tsinghua University;Meituan;Meituan;Tsinghua University",PhD student;Intern;Undergrad student;MS student;MS student;Researcher;Researcher;Associate Professor,https://neurips.cc/virtual/2024/poster/96885,,,https://openreview.net/forum?id=168NLzTpw8,
7,91,-0.118134014,0.26676714,2,-0.11663928851106392,0.32384781611338126,"[0.0004833744463139127, 5.77033394331668e-15, 0.994268748569765, 6.05694547518115e-07, 0.005247271289367805]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,181llen2gw,A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks,Vision-Language Model;Fairness;Debias,6.333333333333333,3.6666666666666665,Hoin Jung;Taeuk Jang;Xiaoqian Wang,Purdue University;Purdue University;Purdue University,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96884,,,https://openreview.net/forum?id=181llen2gw,/media/PosterPDFs/NeurIPS%202024/96884.png?t=1731379505.2628894
7,92,-0.19037005,0.30377576,2,-0.11663928851106392,0.32384781611338126,"[4.931211089113399e-06, 8.224897518597292e-19, 0.99953663395607, 5.529682235845886e-09, 0.00045842930315842815]","[0.010078506041796944, 0.0039301084385898605]",0.17703649366106197,18FGRNd0wZ,Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation,tokenization of crystals;language models;materials generation,6.0,3.5,Keqiang Yan;Xiner Li;Hongyi Ling;Kenna Ashen;Carl Edwards;Raymundo Arroyave;Marinka Zitnik;Heng Ji;Xiaofeng Qian;Xiaoning Qian;Shuiwang Ji,"Texas A&M University;Texas A&M University - College Station;Texas A&M University - College Station;Texas A&M University - College Station;Genentech;Texas A&M University Main Campus;Harvard University;University of Illinois, Urbana-Champaign;Texas A&M University;Texas A&M;Texas A&M University",PhD student;PhD student;PhD student;PhD student;Intern;Assistant Professor;Full Professor;Associate Professor;Full Professor;Professor,https://neurips.cc/virtual/2024/poster/96883,,,https://openreview.net/forum?id=18FGRNd0wZ,/media/PosterPDFs/NeurIPS%202024/96883.png?t=1733428872.6393995
7,93,-0.18803668,0.09546091,4,-0.1996801020901614,0.0024864258082550324,"[0.0012485769487806321, 1.537043696938923e-11, 0.002031117995430069, 0.0004004664069716348, 0.9963198386334472]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,18RdkSv9h9,FINALLY: fast and universal speech enhancement with studio-like quality,speech enhancement; generative models,6.5,4.75,Nicholas Babaev;Kirill Tamogashev;Azat Saginbaev;Ivan Shchekotov;Hanbin Bae;Hosang Sung;WonJun Lee;Hoon-Young Cho;Pavel Andreev,"Samsung;Skolkovo Institute of Science and Technology;Moscow Institute of Physics and Technology;Samsung;Samsung;Samsung;Higher School of Economics, Higher School of Economics",Researcher;MS student;MS student;Principal Researcher;Researcher;Vice President;MS student,https://neurips.cc/virtual/2024/poster/96882,,,https://openreview.net/forum?id=18RdkSv9h9,/media/PosterPDFs/NeurIPS%202024/96882.png?t=1731683595.700073
7,94,0.32727078,-0.11709024,1,0.392824477738228,-0.0839010650724529,"[0.0014834246113995244, 0.9983753885943387, 2.9789530248960577e-19, 0.0001411867792449314, 1.5016934564436857e-11]","[0.01830432951394131, 0.012389519793163098]",0.19543929189966444,1ATLLgvURu,Learning-Augmented Priority Queues,learning-augmented algorithms;algorithms with predictions;priority queue;shortest paths;Dijkstra,5.75,4.25,Ziyad Benomar;Christian Coester,University of Oxford,Associate Professor,https://neurips.cc/virtual/2024/poster/96881,,,https://openreview.net/forum?id=1ATLLgvURu,
7,95,0.3095995,0.5030761,0,0.08273747157300083,0.016519931061773654,"[0.9988038826077563, 8.576347138777707e-11, 0.0011961121242317185, 5.18053925143782e-09, 1.7093854067579267e-12]","[0.013704567544884048, 0.03464655230665849]",0.20580921187183157,1BZKqZphsW,Risk-Averse Fine-tuning of Large Language Models,Risk Averse Reinforcement Learning;Large Language Model Finetuning,5.8,3.2,Sapana Chaudhary;Ujwal Dinesha;Dileep Kalathil;Srinivas Shakkottai,Texas A&M University;Texas A&M University - College Station;Texas A&M University;Texas A&M,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96880,,,https://openreview.net/forum?id=1BZKqZphsW,/media/PosterPDFs/NeurIPS%202024/96880.png?t=1733328781.5713553
7,96,-0.26364937,-0.38828564,3,-0.13817844936362567,-0.24997137110223888,"[0.02280515355578789, 1.717263900368155e-05, 2.3600120948898657e-28, 0.9771681363183988, 9.537486809508086e-06]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,1CssOqRYyz,Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds,compression;point cloud;diffusion,4.0,4.0,Kai Liu;Kang You;Pan Gao,"Nanjing University of Aeronautics and Astronautics;Nanjing university;Nanjing University of Aeronautics and Astronautics, Tsinghua University",MS student;PhD student;Associate Professor,,,,,
7,97,-0.25224024,-0.31188005,3,-0.13817844936362567,-0.24997137110223888,"[0.020281458384177727, 8.691827308809655e-06, 8.962633654662254e-23, 0.9790055781282951, 0.0007042716602182557]","[0.012995679629235733, 0.012504752990176966]",0.17976801969231204,1Du3mMP5YN,Learning to Shape In-distribution Feature Space for Out-of-distribution Detection,Out-of-distribution Detection,5.75,4.0,Yonggang Zhang;Jie Lu;Bo Peng;Zhen Fang;Yiu-ming Cheung,Hong Kong Baptist University;University of Technology Sydney;University of Technology Sydney,Postdoc;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96879,,,https://openreview.net/forum?id=1Du3mMP5YN,/media/PosterPDFs/NeurIPS%202024/96879.png?t=1731745181.7993424
7,98,-0.30068702,-0.14781809,4,-0.1996801020901614,0.0024864258082550324,"[0.0021939634714877726, 1.659632264840416e-08, 2.698692135462876e-12, 0.16602078632785575, 0.8317852336016351]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,1ELFGSNBGC,Multiview Scene Graph,scene representation; spatial understanding; place recognition; object correspondence; scene graph,5.25,3.25,Juexiao Zhang;Gao Zhu;Sihang Li;Xinhao Liu;Haorui Song;Xinran Tang;Chen Feng,New York University;New York University;New York University;New York University;New York University;New York University;New York University,PhD student;MS student;PhD student;PhD student;MS student;MS student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96878,,,https://openreview.net/forum?id=1ELFGSNBGC,/media/PosterPDFs/NeurIPS%202024/96878.png?t=1731728482.5838113
7,99,-0.09486352,0.005280091,4,-0.1996801020901614,0.0024864258082550324,"[0.08810755947531589, 4.805835925500149e-07, 1.4598863005129742e-06, 0.03943174892118417, 0.8724587511336069]","[0.006921602113882397, 0.005827054212253863]",0.24194698287513,1F32iCJFfa,Schrodinger Bridge Flow for Unpaired Data Translation,unpaired data translation;diffusion models;Schrodinger bridge;bridge matching;stochastic interpolant;flow matching,6.5,4.0,Valentin De Bortoli;Iryna Korshunova;Andriy Mnih;Arnaud Doucet,University of Oxford;Google DeepMind;Google DeepMind;University of Oxford,Postdoc;Researcher;Research Scientist;Full Professor,https://neurips.cc/virtual/2024/poster/96877,,,https://openreview.net/forum?id=1F32iCJFfa,/media/PosterPDFs/NeurIPS%202024/96877.png?t=1731688420.732189
8,0,0.08799766,-0.06060414,0,0.040549653809559626,0.01960725566245699,"[0.8302084352226378, 0.0062258137128953055, 2.2110274229426118e-11, 0.1635607705710611, 4.980471295642239e-06]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,00Sx577BT3,The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning,numerical simulations;fluid-dynamics;partial differential equations;operator learning,6.666666666666667,3.6666666666666665,Ruben Ohana;Michael McCabe;Lucas Thibaut Meyer;Rudy Morel;Fruzsina Julia Agocs;Miguel Beneitez;Marsha Berger;Blakesley Burkhart;Stuart B. Dalziel;Drummond Buschman Fielding;Daniel Fortunato;Jared A. Goldberg;Keiya Hirashima;Yan-Fei Jiang;Rich Kerswell;Suryanarayana Maddu;Jonah M. Miller;Payel Mukhopadhyay;Stefan S. Nixon;Jeff Shen;Romain Watteaux;Bruno Régaldo-Saint Blancard;François Rozet;Liam Holden Parker;Miles Cranmer;Shirley Ho,"Flatiron Institute;University of Colorado, Boulder;INRIA;Flatiron Institute;Flatiron Institute;University of Cambridge;Flatiron Institute;Rutgers University;University of Cambridge;Simons Foundation;Flatiron Institute;Flatiron Institute;Simons Foundation;University of Cambridge;Flatiron Institute/Simons Foundation;Los Alamos National Laboratory;University of California, Berkeley;University of Cambridge;Princeton University;CEA;Flatiron Institute;Flatiron Institute;Flatiron Institute;University of Cambridge;Carnegie Mellon University;The University of Tokyo",Postdoc;PhD student;PhD student;Postdoc;Postdoc;Postdoc;Full Professor;Assistant Professor;Director of the GK Batchelor Laboratory;Postdoc;Researcher;Postdoc;Researcher;Full Professor;Postdoc;Researcher;Postdoc;PhD student;PhD student;Researcher;Postdoc;Intern;Researcher;Assistant Professor;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/97882,,,,
8,1,-0.08406016,0.2851326,2,-0.0929522627625797,0.3325470294663321,"[0.001197809808181474, 8.279296318511602e-16, 0.9969814551276298, 4.972516716804048e-10, 0.0018207345669360696]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,00uVk06eVK,On the Noise Robustness of In-Context Learning for Text Generation,In-Context Learning;Large Language Models;Noise Robustness,6.333333333333333,3.0,Hongfu Gao;Feipeng Zhang;Wenyu Jiang;Jun Shu;Feng Zheng;Hongxin Wei,Xi'an Jiaotong University;Xi'an Jiaotong University;Nanjing University;Xi'an Jiaotong University;Southern University of Science and Technology;Southern University of Science and Technology,MS student;Full Professor;PhD student;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96962,,,https://openreview.net/forum?id=00uVk06eVK,/media/PosterPDFs/NeurIPS%202024/96962.png?t=1731587881.4159098
8,2,-0.16364236,-0.11411294,4,-0.22277274633914645,0.00022583470936325936,"[0.40208186605953866, 5.157685119666026e-07, 2.337324803688525e-10, 0.16419899458892098, 0.43371862334929595]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,01I55gys19,Few-Class Arena: A Benchmark for Efficient Vision Model Selection and Dataset Difficulty,few-class;efficiency;neural network;convolutional neural network;transformer;dataset difficulty measurement;scaling law,5.0,3.3333333333333335,Bryan Bo Cao;Lawrence O'Gorman;Michael Coss;Shubham Jain,Nokia networks GmbH;State University of New York at Stony Brook,Intern;Assistant Professor,,,,,
8,3,0.07371062,-0.27021888,3,-0.1122552559510126,-0.2630561550953563,"[0.014388752627308436, 0.14851537256461902, 4.95590602319237e-23, 0.837095873442339, 1.3657334520293562e-09]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,01XV5Za56k,Testing Calibration in Nearly-Linear Time,Calibration;Property testing;Linear programming,6.25,3.25,Lunjia Hu;Arun Jambulapati;Kevin Tian;Chutong Yang,Stanford University;Stanford University;Stanford University;University of Texas at Austin,PhD student;PhD student;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96961,,,https://openreview.net/forum?id=01XV5Za56k,
8,4,-0.1284643,0.3103237,2,-0.0929522627625797,0.3325470294663321,"[8.400363543678723e-05, 1.830477649489986e-18, 0.9992311251690691, 1.0641840071147752e-11, 0.0006848711848525223]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,01lhHg8H9p,GLBench: A Comprehensive Benchmark for Graph with Large Language Models,Graph learning;Large Language Model;Zero-Shot,6.75,4.0,Yuhan Li;Peisong Wang;Xiao Zhu;Aochuan Chen;Haiyun Jiang;Deng Cai;Victor Wai Kin Chan;Jia Li,"Hong Kong University of Science and Technology;Tsinghua University;Beijing University of Posts and Telecommunications;Hong Kong University of Science and Technology;Tencent AI Lab;Tencent AI Lab;Shenzhen International Graduate School, Tsinghua University;Hong Kong University of Science and Technology",PhD student;MS student;Undergrad student;PhD student;Researcher;Research Scientist;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97881,,,,/media/PosterPDFs/NeurIPS%202024/97881.png?t=1731478194.2539835
8,5,-0.23808402,0.26056772,2,-0.0929522627625797,0.3325470294663321,"[2.678364028752705e-05, 2.863156267626102e-20, 0.9939149276745648, 1.9938820583586403e-11, 0.006058288665208969]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,01qa1ZJs65,Bridge the Modality and Capability Gaps in Vision-Language Model Selection,Vision-Language Model;Model Selection;Zero-Shot Image Classification,5.25,4.0,Chao Yi;Yuhang He;De-Chuan Zhan;Han-Jia Ye,Nanjing University;Nanjing University;Nanjing University;Nanjing University,MS student;Undergrad student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96960,,,https://openreview.net/forum?id=01qa1ZJs65,/media/PosterPDFs/NeurIPS%202024/96960.png?t=1731123927.9174762
8,6,-0.10493148,-0.30384988,3,-0.1122552559510126,-0.2630561550953563,"[0.014186681877128049, 0.0004128692828916761, 3.5003207755041067e-22, 0.985389693270424, 1.0755569556313772e-05]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,01s5ODIHKd,FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space,deep watermarking;latent frequency optimization,5.5,3.75,YiYang Guo;Ruizhe Li;Mude Hui;Hanzhong Allan Guo;Chen Zhang;Chuangjian Cai;Le Wan;Shangfei Wang,"University of Science and Technology of China;University of California, Santa Cruz;Renmin University of China;Tsinghua University;University of Science and Technology of China;University of Science and Technology of China",MS student;PhD student;MS student;PhD student;Full Professor;PhD student,https://neurips.cc/virtual/2024/poster/96959,,,https://openreview.net/forum?id=01s5ODIHKd,/media/PosterPDFs/NeurIPS%202024/96959.png?t=1730176108.8718698
8,7,-0.295713,-0.42771262,3,-0.1122552559510126,-0.2630561550953563,"[0.0014430523735476032, 2.2151181754259713e-06, 3.777926024261139e-27, 0.9985521562424251, 2.576265851832587e-06]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,02CIZ8qeDc,PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection,3D anomaly detection;Zero-shot 3D anomaly detection,6.0,3.6666666666666665,Qihang Zhou;Jiangtao Yan;Shibo He;Wenchao Meng;Jiming Chen,Zhejiang University;Zhejiang University;Zhejiang University;Zhejiang University,PhD student;MS student;Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96958,,,https://openreview.net/forum?id=02CIZ8qeDc,/media/PosterPDFs/NeurIPS%202024/96958.png?t=1731476864.9817398
8,8,-0.3188932,-0.023905918,4,-0.22277274633914645,0.00022583470936325936,"[0.007612073749021442, 1.6250712803369258e-13, 8.434151161204897e-06, 0.0001483196919078173, 0.9922311724077469]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,02HWT9c4Lp,Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion,Semantic Scene completion，Voxel Proposal，Knowledge Distillation,5.5,4.0,Lubo Wang;Di Lin;Kairui Yang;Ruonan Liu;Qing Guo;Wuyuan Xie;Miaohui Wang;Lingyu Liang;Yi Wang;Ping Li,"Tianjin University;Tianjin University;Tianjin University;Tianjin University; Agency for Science, Technology and Research (A*STAR));Department of Software Engineering, Shenzhen University;Shenzhen University;South China University of Technology;Shenzhen University;The Hong Kong Polytechnic University",MS student;Associate Professor;PhD student;Associate Professor;Researcher;Associate Professor;Associate Professor;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96957,,,https://openreview.net/forum?id=02HWT9c4Lp,/media/PosterPDFs/NeurIPS%202024/96957.png?t=1731159292.6143699
8,9,0.52375084,0.03593809,1,0.4005834145426374,-0.08249288779183311,"[6.585662171752935e-05, 0.9999250396314662, 1.8811508303027798e-16, 9.103746815902094e-06, 2.217361284121322e-29]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,02r24A8doi,Achieving Constant Regret in Linear Markov Decision Processes,Reinforcement learning;Constant regret;Misspecified linear MDP,5.25,2.75,Weitong Zhang;Zhiyuan Fan;Jiafan He;Quanquan Gu,"Massachusetts Institute of Technology;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles",PhD student;PhD student;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96956,,,https://openreview.net/forum?id=02r24A8doi,
8,10,-0.24769914,0.06194072,4,-0.22277274633914645,0.00022583470936325936,"[0.007214565160140028, 7.86888984729632e-14, 0.0007450816317839207, 9.055653320692332e-06, 0.9920312975546766]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,04EC4ZnZJj,MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers,transformer architecture;large language model;computational complexity reduction,6.0,3.5,Ning Ding;Yehui Tang;Haochen Qin;Zhenli Zhou;Chao Xu;Lin Li;Kai Han;Liao Heng;Yunhe Wang,"Peking University;Huawei Technologies Ltd.;Huawei Technologies Ltd.;Peking University;Peking University;Huawei Noah's Ark Lab;, Tsinghua University;Huawei Noah's Ark Lab",PhD student;Researcher;Researcher;MS student;Full Professor;Principal Researcher;Principal Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96955,,,https://openreview.net/forum?id=04EC4ZnZJj,
8,11,0.45866024,0.07679337,1,0.4005834145426374,-0.08249288779183311,"[0.00394873039422702, 0.9959687123201912, 1.4980809307163317e-12, 8.255728408370711e-05, 1.3235878561785983e-23]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,06JRFVK88O,Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games,Multi-agent Reinforcement Learning;Imitation Learning,6.666666666666667,3.0,The Viet Bui;Tien Anh Mai;Thanh Hong Nguyen,Singapore Management University;University of Oregon;Singapore Management University,Assistant Professor;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96954,,,https://openreview.net/forum?id=06JRFVK88O,/media/PosterPDFs/NeurIPS%202024/96954.png?t=1731744891.8886228
8,12,-0.21952832,-0.2596673,3,-0.1122552559510126,-0.2630561550953563,"[0.05130382173463168, 2.426652635448246e-06, 2.2401678486323302e-17, 0.9415398173282133, 0.0071539342845193]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,06Vt6f2js7,SyncTweedies: A General Generative Framework Based on Synchronized Diffusions,Diffusion Models;Synchronization;Texturing;3D Gaussian Splatting;Mesh;Panorama,6.666666666666667,3.6666666666666665,Jaihoon Kim;Juil Koo;Kyeongmin Yeo;Minhyuk Sung,KAIST;Adobe Systems;Korea Advanced Institute of Science & Technology;Korea Advanced Institute of Science & Technology,MS student;Intern;Undergrad student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96953,,,https://openreview.net/forum?id=06Vt6f2js7,
8,13,0.5387558,-0.021885695,1,0.4005834145426374,-0.08249288779183311,"[5.252733948189762e-06, 0.9999894355417875, 5.251005541457718e-20, 5.311724264307896e-06, 8.865756526829892e-32]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,07N0qoaZ2L,Improved Analysis for Bandit Learning in Matching Markets,Bandits;Matching markets;Stable matching;Stable regret;Exploration and exploitation;$\alpha$-condition,5.5,3.0,Fang Kong;Zilong Wang;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;John Hopcroft Center, Shanghai Jiao Tong University",PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96952,,,https://openreview.net/forum?id=07N0qoaZ2L,/media/PosterPDFs/NeurIPS%202024/96952.png?t=1731746661.9360106
8,14,-0.31746334,-0.03755091,4,-0.22277274633914645,0.00022583470936325936,"[0.009444159303795923, 4.052453754994829e-13, 2.8927906631733412e-06, 0.0002843728632723007, 0.9902685750418634]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,08A6X7FSTs,Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text,Text-to-3D Scene Generation;Latent Diffusion Models,5.5,4.5,Xinyang Li;Zhangyu Lai;Linning Xu;Yansong Qu;Liujuan Cao;Shengchuan Zhang;Bo Dai;Rongrong Ji,Xiamen University;Xiamen University;Xiamen University;Xiamen University;Xiamen University;Shanghai AI Laboratory;Xiamen University;The Chinese University of Hong Kong,PhD student;MS student;PhD student;Full Professor;Assistant Professor;Scientist;Full Professor;Ph.D. student,https://neurips.cc/virtual/2024/poster/96951,,,https://openreview.net/forum?id=08A6X7FSTs,/media/PosterPDFs/NeurIPS%202024/96951.png?t=1732593534.8700738
8,15,0.21572201,0.15297481,0,0.040549653809559626,0.01960725566245699,"[0.9993106603966413, 0.00036637998483975603, 4.5437861689780583e-05, 0.0002775194224729978, 2.3343562586522975e-09]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,08GbdALmEs,Learning Versatile Skills with Curriculum Masking,reinforcement learning;unsupervised pretraining;masked prediction;curriculum learning,5.25,3.25,Yao Tang;Zhihui Xie;Zichuan Lin;Deheng Ye;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;Tencent AI Lab;Tencent;John Hopcroft Center, Shanghai Jiao Tong University",Undergrad student;MS student;Researcher;Principal Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96950,,,https://openreview.net/forum?id=08GbdALmEs,/media/PosterPDFs/NeurIPS%202024/96950.png?t=1733319308.3295946
8,16,-0.17784788,-0.16018736,3,-0.1122552559510126,-0.2630561550953563,"[0.32489152461343496, 1.5469133435342912e-06, 2.5117462095546436e-12, 0.4760721835895713, 0.19903474488113834]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,08nbMTxazb,Chicks4FreeID: A Benchmark Dataset for Chicken Re-Identification,animal re-identification;chicken re-identification;chicken dataset;re-identification dataset;benchmark dataset;closed-set re-identification;computer vision;chicken instance segmentation;poultry;livestock,4.75,4.0,Daria Kern;Tobias Schiele;Ulrich Klauck;Winfred Ingabire,Glasgow Caledonian University;Hochschule Aalen;Glasgow Caledonian University,PhD student;Full Professor;Lecturer,,,,,
8,17,0.12485067,-0.17534988,3,-0.1122552559510126,-0.2630561550953563,"[0.0997946880603351, 0.26280216385256466, 5.071432254245357e-18, 0.6374031449436758, 3.143424450151167e-09]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,08oUnmtj8Q,FSEO: A Few-Shot Evolutionary Optimization Framework for Expensive Multi-Objective Optimization and Constrained Optimization,Expensive optimization;few-shot optimization;multi-objective optimization;constrained optimization;surrogate-assisted evolutionary optimization,4.5,3.5,Xunzhao Yu,,,,,,,
8,18,-0.045080878,-0.32160506,3,-0.1122552559510126,-0.2630561550953563,"[0.007881416022209974, 0.004784877196085897, 2.2912702605006954e-24, 0.9873335097663265, 1.9701537751515965e-07]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,09RKw0vXjR,Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations,feature selection;sparse coding;dictionary learning;compressed sensing;iterative hard thresholding;pruning method,5.75,3.0,Yasutoshi Ida;Sekitoshi Kanai;Atsutoshi Kumagai;Tomoharu Iwata;Yasuhiro Fujiwara,NTT;NTT;NTT;NTT;NTT,Researcher;Researcher;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96949,,,https://openreview.net/forum?id=09RKw0vXjR,/media/PosterPDFs/NeurIPS%202024/96949.png?t=1733375377.8112724
8,19,-0.29219365,-0.1354431,4,-0.22277274633914645,0.00022583470936325936,"[0.06852957190418317, 7.577845058303262e-10, 5.646433692115109e-10, 0.04053022734009475, 0.8909401994332943]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,09nyBqSdUz,RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance,Consistent image generation;Diverse image generation;Improve temporal-consistency;Feature injection from multiple images,5.5,4.0,Jiaojiao Fan;Haotian Xue;Qinsheng Zhang;Yongxin Chen,Georgia Institute of Technology;Georgia Institute of Technology;Georgia Institute of Technology;NVIDIA,PhD student;PhD student;Associate Professor;Research Intern,https://neurips.cc/virtual/2024/poster/96948,,,https://openreview.net/forum?id=09nyBqSdUz,/media/PosterPDFs/NeurIPS%202024/96948.png?t=1731392354.7708242
8,20,0.22983314,0.005944166,0,0.040549653809559626,0.01960725566245699,"[0.7787426458820457, 0.1826679580642973, 1.757428353132777e-10, 0.03858939576333075, 1.1458337418228819e-10]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0AumdfLzpK,A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations,Visual Reinforcement Learning;Generalization,6.0,4.0,Wonil Song;Hyesong Choi;Kwanghoon Sohn;Dongbo Min,Yonsei Univ.;Ewha Womans University;Yonsei University;Ewha Womans University,PhD student;PhD student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96947,,,https://openreview.net/forum?id=0AumdfLzpK,/media/PosterPDFs/NeurIPS%202024/96947.png?t=1732451612.1247888
8,21,-0.2313607,0.15489271,4,-0.22277274633914645,0.00022583470936325936,"[0.004241994162645978, 1.1965890479043515e-15, 0.2140838050970502, 1.9531590638843647e-07, 0.7816740054243962]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,0AwMciNShl,"Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality",Human evaluation;text-to-video models,5.25,4.0,Tianle Zhang;Langtian Ma;Yuchen Yan;Yuchen Zhang;Yue Yang;Ziyao Guo;Wenqi Shao;Kai Wang;Yang You;Yu Qiao;Ping Luo;Kaipeng Zhang,University of Electronic Science and Technology of China;Southern University of Science and Technology;The University of Nottingham Ningbo China;University of Electronic Science and Technology of China;Xidian University;Shanghai AI Laboratory;National University of Singapore;National University of Singapore;Shanghai AI Laboratory;The University of Hong Kong;Shanghai Jiaotong University,Undergrad student;Undergrad student;Undergrad student;Undergrad student;MS student;Researcher;PhD student;Professor;Researcher;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96946,,,https://openreview.net/forum?id=0AwMciNShl,/media/PosterPDFs/NeurIPS%202024/96946.png?t=1729079669.652648
8,22,0.44196302,-0.22339565,1,0.4005834145426374,-0.08249288779183311,"[3.6676890336729973e-07, 0.9999451224078912, 1.0269504998196152e-29, 5.451082320542472e-05, 2.4899540855019127e-29]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0C3bLHwjsY,Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions,Online Matching;Competitive Analysis;Fairness Maximization,6.25,3.0,Will Ma;Pan Xu,Columbia University;New Jersey Institute of Technology,Assistant Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96945,,,https://openreview.net/forum?id=0C3bLHwjsY,/media/PosterPDFs/NeurIPS%202024/96945.png?t=1731641014.5806563
8,23,0.31953293,-0.23248373,1,0.4005834145426374,-0.08249288779183311,"[2.6666629622513823e-05, 0.9977770628881237, 5.957534152787461e-27, 0.0021962704822537206, 2.4590679253512213e-21]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0DE1dLMW2b,Quantum algorithm for large-scale market equilibrium computation,market equilibrium computation;quantum algorithm,6.0,2.75,Po-Wei Huang;Patrick Rebentrost,Centre for Quantum Technologies;National University of Singapore,Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96944,,,https://openreview.net/forum?id=0DE1dLMW2b,/media/PosterPDFs/NeurIPS%202024/96944.png?t=1731426989.5298698
8,24,0.0025802255,-0.08199731,0,0.040549653809559626,0.01960725566245699,"[0.7897638301864343, 0.00036122318979292116, 3.814242766710219e-11, 0.20905318111875787, 0.000821765466872305]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0EfUYVMrLv,Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment,non-stationary environments;continuous distribution shift;test-time adaptation;unlabeled data,6.666666666666667,4.0,Zhen-Yu Zhang;Zhiyu Xie;Huaxiu Yao;Masashi Sugiyama,"RIKEN;Stanford University;Department of Computer Science, University of North Carolina at Chapel Hill;The University of Tokyo",Postdoc;MS student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96943,,,https://openreview.net/forum?id=0EfUYVMrLv,/media/PosterPDFs/NeurIPS%202024/96943.png?t=1731687693.6296034
8,25,0.023439856,-0.079839304,0,0.040549653809559626,0.01960725566245699,"[0.7872405468706387, 0.00080650738678446, 2.3987316109483488e-11, 0.2117090859396382, 0.00024385977895141622]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0G0VpMjKyV,Sketching for Distributed Deep Learning: A Sharper Analysis,sketching;distributed learning;federated learning;optimization,5.666666666666667,4.0,Mayank Shrivastava;Berivan Isik;Qiaobo Li;Sanmi Koyejo;Arindam Banerjee,"University of Illinois, Urbana Champaign;Stanford University;Department of Computer Science, University of Illinois at Urbana-Champaign;University of Illinois, Urbana Champaign;Google",MS student;PhD student;PhD student;Professor;Research Scientist,https://neurips.cc/virtual/2024/poster/96942,,,https://openreview.net/forum?id=0G0VpMjKyV,/media/PosterPDFs/NeurIPS%202024/96942.png?t=1733481266.9121125
8,26,-0.06371302,0.3954228,2,-0.0929522627625797,0.3325470294663321,"[1.6492993040288845e-05, 1.333750753436512e-19, 0.9999789175062275, 6.557369395215103e-14, 4.58950066654032e-06]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,0G5OK5vmmg,WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts,Benchmark;Large Language Models;Classical Chinese Literature and Language Arts,6.25,2.75,Jiahuan Cao;Yang Liu;Yongxin Shi;Kai Ding;Lianwen Jin,South China University of Technology;South China University of Technology;South China University of Technology;INTSIG Information;South China University of Technology,MS student;MS student;PhD student;Researcher;Professor,https://neurips.cc/virtual/2024/poster/97880,,,,/media/PosterPDFs/NeurIPS%202024/97880.png?t=1730896668.2191207
8,27,-0.2963673,0.015343715,4,-0.22277274633914645,0.00022583470936325936,"[0.005652005204063609, 5.539749697559721e-14, 7.978201119959784e-05, 3.163623213917802e-05, 0.9942365765525423]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,0G8AXwtmy2,T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition,harmful dataset;harmful content detection;Vision Language Model,6.5,3.75,Chen Yeh;You-Ming Chang;Wei-Chen Chiu;Ning Yu,National Yang Ming Chiao Tung University;National Yang Ming Chiao Tung University;National Chiao Tung University,MS student;MS student;Associate Professor,https://neurips.cc/virtual/2024/poster/97879,,,,/media/PosterPDFs/NeurIPS%202024/97879.png?t=1730218737.4487233
8,28,0.08612508,0.3898904,2,-0.0929522627625797,0.3325470294663321,"[0.001449390413984016, 2.940796910083983e-14, 0.998550541016213, 1.3767384288996629e-11, 6.85560061214875e-08]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,0Gl5WxY6es,Grounding Multimodal Large Language Models in Actions,Embodied AI;Multimodal Large Language Models;Reinforcement Learning;Imitation Learning,6.0,3.6666666666666665,Andrew Szot;Bogdan Mazoure;Harsh Agrawal;R Devon Hjelm;Zsolt Kira;Alexander T Toshev,Georgia Institute of Technology;Apple;Apple;Apple;Georgia Institute of Technology;Apple,PhD student;Research Scientist;Researcher;Researcher;Assistant Professor;research scientist,https://neurips.cc/virtual/2024/poster/96941,,,https://openreview.net/forum?id=0Gl5WxY6es,
8,29,-0.20296153,0.2345368,2,-0.0929522627625797,0.3325470294663321,"[0.00036577845560349735, 8.365108304835712e-18, 0.9607716314600323, 8.359994668888922e-10, 0.03886258924836462]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,0Gmi8TkUC7,GenAI Arena: An Open Evaluation Platform for Generative Models,Evaluation;Benchmark;Platform;Generative Model,6.0,3.5,Dongfu Jiang;Max Ku;Tianle Li;Yuansheng Ni;Shizhuo Sun;Rongqi Fan;Wenhu Chen,Allen Institute for Artificial Intelligence;University of Waterloo;University of Waterloo;University of Toronto;NVIDIA;University of Waterloo,Intern;MS student;MS student;Undergrad student;Intern;Assistant Professor,https://neurips.cc/virtual/2024/poster/97878,,,,/media/PosterPDFs/NeurIPS%202024/97878.png?t=1730329031.3167162
8,30,-0.3021013,-0.23802479,3,-0.1122552559510126,-0.2630561550953563,"[0.08678386586094423, 5.0846579559937456e-08, 1.281575124389264e-14, 0.8123597935323391, 0.10085628976012442]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,0HRRNEAQFp,A General Protocol to Probe Large Vision Models for 3D Physical Understanding,3D physical scene understanding; Representation probing protocol; Benchmark and evaluation,6.333333333333333,4.0,Guanqi Zhan;Chuanxia Zheng;Weidi Xie;Andrew Zisserman,University of Oxford;University of Oxford;Shanghai Jiaotong University,PhD student;Postdoc;Associate Professor,https://neurips.cc/virtual/2024/poster/96940,,,https://openreview.net/forum?id=0HRRNEAQFp,/media/PosterPDFs/NeurIPS%202024/96940.png?t=1731705235.0575316
8,31,0.40233114,0.06031101,1,0.4005834145426374,-0.08249288779183311,"[0.022332030182062798, 0.977123881510209, 7.569472238911694e-12, 0.0005440883001587392, 6.827251534999094e-20]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0JSKjdePGq,When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL,reinforcement learning;continuous-time,6.75,3.25,Lenart Treven;Bhavya Sukhija;Yarden As;Florian Dorfler;Andreas Krause,"Swiss Federal Institute of Technology;ETHZ - ETH Zurich;Department of Computer Science, ETHZ - ETH Zurich;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96939,,,https://openreview.net/forum?id=0JSKjdePGq,/media/PosterPDFs/NeurIPS%202024/96939.png?t=1730197260.75527
8,32,-0.31179968,-0.050893012,4,-0.22277274633914645,0.00022583470936325936,"[0.01225941277539042, 1.2616747973239824e-12, 8.839843383561416e-07, 0.0005649672328469543, 0.9871747360061627]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,0KseSacluJ,CoFie: Learning Compact Neural Surface Representations with Coordinate Fields,Neural Surface Representation;Shape Auto-Decoding;Coordinate Field.,5.0,4.0,Hanwen Jiang;Haitao Yang;Georgios Pavlakos;Qixing Huang,University of Texas at Austin;The University of Texas at Austin;University of Texas at Austin;University of Texas at Austin,PhD student;PhD student;Assistant Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96938,,,https://openreview.net/forum?id=0KseSacluJ,
8,33,0.11298243,0.035079706,0,0.040549653809559626,0.01960725566245699,"[0.9893028319782465, 0.0004781311689370663, 7.77749030561764e-08, 0.010214874582997078, 4.084494916191791e-06]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0KvYLaTBTE,Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference,Generative models;Reinforcement learning;Decision transformer,6.333333333333333,3.0,Deqian Kong;Dehong Xu;Minglu Zhao;Bo Pang;Jianwen Xie;Andrew Lizarraga;Yuhao Huang;Sirui Xie;Ying Nian Wu,"University of California, Los Angeles;Amazon;University of California, Los Angeles;University of California, Los Angeles;Xi'an Jiaotong University;University of California, Los Angeles;University of California, Los Angeles;UCLA",PhD student;Intern;PhD student;PhD student;PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96937,,,https://openreview.net/forum?id=0KvYLaTBTE,
8,34,-0.23456638,0.06657637,4,-0.22277274633914645,0.00022583470936325936,"[0.00898974006264897, 1.4674731139186403e-13, 0.0008284852149715498, 9.859885038235963e-06, 0.9901719148371947]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,0LXotew9Du,KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization,Quantization;KV Cache;LLM Inference;Compression;Long Context Length,6.25,3.25,Coleman Richard Charles Hooper;Sehoon Kim;Hiva Mohammadzadeh;Michael W. Mahoney;Sophia Shao;Kurt Keutzer;Amir Gholami,"University of California, Berkeley;University of California, Berkeley;University of California, Berkeley;University of California, Berkeley",PhD student;PhD student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96936,,,https://openreview.net/forum?id=0LXotew9Du,
8,35,0.11017645,-0.16371755,3,-0.1122552559510126,-0.2630561550953563,"[0.1588833720780159, 0.15088612242041005, 4.65685540018652e-17, 0.6902304849236983, 2.0577875669344835e-08]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,0Lb8vZT1DB,Reliable Learning of Halfspaces under Gaussian Marginals,reliable learning;agnostic learning;halfspace;proper leaning;statistical query,7.25,2.25,Ilias Diakonikolas;Lisheng Ren;Nikos Zarifis,"University of Wisconsin - Madison;University of Wisconsin - Madison;University of Wisconsin, Madison",Full Professor;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96935,,,https://openreview.net/forum?id=0Lb8vZT1DB,
8,36,0.1429859,0.059452157,0,0.040549653809559626,0.01960725566245699,"[0.9941223349244173, 0.0006656806836515615, 2.5337944740401964e-07, 0.005211197781120279, 5.3323136330911e-07]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0LfgE6kvKZ,Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning,Federated Learning; Model Merging,5.0,3.6666666666666665,Minghui Chen;Meirui Jiang;Xin Zhang;Qi Dou;Zehua Wang;Xiaoxiao Li,"University of British Columbia;Meta Facebook;The Chinese University of Hong Kong;University of British Columbia;University of British Columbia;Department of Computer Science and Engineering, The Chinese University of Hong Kong",PhD student;Research Scientist;Assistant Professor;Researcher;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96934,,,https://openreview.net/forum?id=0LfgE6kvKZ,/media/PosterPDFs/NeurIPS%202024/96934.png?t=1731518093.5294044
8,37,-0.040502112,0.02318828,0,0.040549653809559626,0.01960725566245699,"[0.9368883713946831, 8.203606077318925e-07, 3.0906505989477672e-06, 0.007632360794925625, 0.05547535679918462]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0Lr9HQijA1,Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations,Imprecise Label Learning,5.75,3.0,Hao Chen;Ankit Shah;Jindong Wang;Ran Tao;Yidong Wang;Xiang Li;Xing Xie;Masashi Sugiyama;Rita Singh;Bhiksha Raj,"Carnegie Mellon University;Accenture;Microsoft Research;Peking University;Microsoft Research Asia;The University of Tokyo;School of Computer Science, Carnegie Mellon University;Mohamed bin Zayed University of Artificial Intelligence",PhD student;Principal Researcher;Researcher;PhD student;Senior Principal Researcher;Full Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96933,,,https://openreview.net/forum?id=0Lr9HQijA1,/media/PosterPDFs/NeurIPS%202024/96933.png?t=1731704880.9846606
8,38,-0.06471333,0.08954511,0,0.040549653809559626,0.01960725566245699,"[0.7160173024561282, 1.1427025506227527e-08, 0.0011360135291393204, 0.0005544812993192823, 0.2822921912883878]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0MXzbAv8xy,GFT: Graph Foundation Model with Transferable Tree Vocabulary,Graph Foundation Model;Transferability;Computation Tree;Graph Neural Network,6.0,3.75,Zehong Wang;Zheyuan Zhang;Nitesh V Chawla;Chuxu Zhang;Yanfang Ye,University of Notre Dame;University of Notre Dame;University of Notre Dame;University of Notre Dame,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96932,,,https://openreview.net/forum?id=0MXzbAv8xy,
8,39,0.06407858,0.09707585,0,0.040549653809559626,0.01960725566245699,"[0.9987114438714584, 4.134966913889465e-06, 5.091985109890276e-05, 0.0009770610050236115, 0.0002564403055051473]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0NMzBwqaAJ,Not All Tokens Are What You Need for Pretraining,pre-training;next token prediction;data optimization;data selection,7.666666666666667,4.0,Zhenghao Lin;Zhibin Gou;Yeyun Gong;Xiao Liu;yelong shen;Ruochen Xu;Chen Lin;Yujiu Yang;Jian Jiao;Nan Duan;Weizhu Chen,Xiamen University;Microsoft;Microsoft Research Asia;Microsoft Research;Xiamen University;Tsinghua University;Microsoft;Microsoft Research Asia;Microsoft GenAI,MS student;Intern;Researcher;Researcher;Full Professor;Full Professor;Principal Researcher;Principal Researcher;Vice President,https://neurips.cc/virtual/2024/poster/96931,,,https://openreview.net/forum?id=0NMzBwqaAJ,/media/PosterPDFs/NeurIPS%202024/96931.png?t=1733724962.7310221
8,40,-0.021407472,0.09407413,0,0.040549653809559626,0.01960725566245699,"[0.9554457711961715, 9.164428825291073e-08, 0.0005346967849487993, 0.0007350029330524272, 0.043284437441539016]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0NQzQVu9tY,DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors,representation learning;offline reinforcement learning;behavioral cloning;visual distractor,7.0,3.0,Joseph Ortiz;Antoine Dedieu;Wolfgang Lehrach;J Swaroop Guntupalli;Carter Wendelken;Ahmad Humayun;Sivaramakrishnan Swaminathan;Guangyao Zhou;Miguel Lazaro-Gredilla;Kevin Patrick Murphy,Google DeepMind;Google DeepMind;Google Deepmind;Google DeepMind;Google;Google DeepMind;Google DeepMind;Google DeepMind;Google Deepmind;Google,Researcher;Researcher;Researcher;Researcher;Researcher;Researcher;Research Engineer;Research Scientist;Research Scientist;Principal Researcher,https://neurips.cc/virtual/2024/poster/97877,,,,/media/PosterPDFs/NeurIPS%202024/97877.png?t=1733266397.4133346
8,41,-0.056248758,0.025906589,0,0.040549653809559626,0.01960725566245699,"[0.8755409686436496, 3.3572573201580005e-07, 6.100181612867494e-06, 0.006171973534943566, 0.11828062191406198]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0SMhqvgHST,EEVEE and GATE: Finding the right benchmarks and how to run them seamlessly,multi-modal;benchmarks;machine learning;model evaluation;benchmark frameworks,6.0,4.0,Antreas Antoniou;Eleni Triantafillou;Hugo Larochelle;Sebastien Montella;Fady Rezk;Kiyoon Kim;Linus Ericsson;Pavlos Vougiouklis;Justin Engelmann;Elliot J. Crowley;Srihari Humbarwadi;Yi Liu;Guang Yang;Jeff Z. Pan;Amos Storkey,"Google;Google;Huawei Technologies Ltd.;Samsung;Deargen;University of Edinburgh, University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh, University of Edinburgh;University of Edinburgh",Researcher;Research Scientist;Researcher;Intern;Researcher;Postdoc;Researcher;Assistant Professor;Researcher;Full Professor;Full Professor,,,,,
8,42,-0.15132618,0.02146309,4,-0.22277274633914645,0.00022583470936325936,"[0.12974901597118685, 8.025728036547888e-10, 1.557371579731853e-05, 0.0007969263380792635, 0.8694384831723636]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,0SRJBtTNhX,IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors,Graph Machine Learning;Graph Data Augmentation;Graph Neural Networks,5.5,4.0,Shenghe Zheng;Hongzhi Wang;Xianglong Liu,Harbin Institute of Technology;Harbin Institute of Technology;Harbin Institute of Technology,MS student;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96930,,,https://openreview.net/forum?id=0SRJBtTNhX,/media/PosterPDFs/NeurIPS%202024/96930.png?t=1732617637.3891017
8,43,-0.18518934,0.0027779788,4,-0.22277274633914645,0.00022583470936325936,"[0.06093103845779585, 1.842484027090417e-10, 4.861464076981402e-06, 0.000636955248658512, 0.9384271446452204]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,0T8xRFrScB,Benchmarking Counterfactual Image Generation,benchmark;causal inference;counterfactual image generation,7.25,3.75,Thomas Melistas;Nikos Spyrou;Nefeli Gkouti;Pedro Sanchez;Athanasios Vlontzos;Yannis Panagakis;Giorgos Papanastasiou;Sotirios A. Tsaftaris,"University of Athens;University of Athens;University of Athens;University of Edinburgh, University of Edinburgh;Spotify;Pfizer;University of Edinburgh",PhD student;PhD student;PhD student;PhD student;Researcher;Principal Researcher;Professor in machine learning and computer vision,https://neurips.cc/virtual/2024/poster/97876,,,,/media/PosterPDFs/NeurIPS%202024/97876.png?t=1731712408.6398222
8,44,0.5118622,-0.024860546,1,0.4005834145426374,-0.08249288779183311,"[1.3749744681303489e-05, 0.9999739391105792, 1.8292993493557601e-19, 1.2311144739392825e-05, 9.336110569855818e-30]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0TUMAAb3of,Queueing Matching Bandits with Preference Feedback,Bandits;Queue;Preference Feedback,6.0,2.5,Jung-hun Kim;Min-hwan Oh,Seoul National University;Seoul National University,Assistant Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96929,,,https://openreview.net/forum?id=0TUMAAb3of,/media/PosterPDFs/NeurIPS%202024/96929.png?t=1733803835.532587
8,45,-0.0018669573,0.3644946,2,-0.0929522627625797,0.3325470294663321,"[0.00034932117439640903, 3.00352874791531e-16, 0.9996453131771568, 6.847492288175656e-12, 5.365641599146257e-06]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,0VeSCjRDBy,Adversarial Moment-Matching Distillation of Large Language Models,Knowledge distillation;Large language models;Imitation learning;Moment-matching;Adversarial training,6.25,3.0,Chen Jia,,,https://neurips.cc/virtual/2024/poster/96928,,,https://openreview.net/forum?id=0VeSCjRDBy,/media/PosterPDFs/NeurIPS%202024/96928.png?t=1731660620.7591212
8,46,-0.24925767,0.015651966,4,-0.22277274633914645,0.00022583470936325936,"[0.011599844060333937, 1.0137662548499824e-12, 2.87546897014105e-05, 6.945374388422516e-05, 0.9883019475050665]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,0WCFI2Qx85,ScaleKD: Strong Vision Transformers Could Be Excellent Teachers,knowledge distillation;model compression;training acceleration;vision transformer;convolutional neural network;multi-layer perception,6.25,4.5,Jiawei Fan;Chao Li;Xiaolong Liu;Anbang Yao,Intel Labs China;Intel;Intel,Research Intern;Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96927,,,https://openreview.net/forum?id=0WCFI2Qx85,/media/PosterPDFs/NeurIPS%202024/96927.png?t=1731695837.2500114
8,47,0.2804453,-0.1894261,1,0.4005834145426374,-0.08249288779183311,"[0.0004860918890854463, 0.989163831969928, 5.2195531815561736e-23, 0.01035007614098655, 9.096436118596116e-18]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0XKvW4ijxp,Learning-Augmented Algorithms with Explicit Predictors,online algorithms;learning-augmented algorithms;scheduling;caching,6.0,4.0,Marek Elias;Haim Kaplan;Yishay Mansour;Shay Moran,"Bocconi University;Technion, Technion;School of Computer Science, Tel Aviv University",Assistant Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96926,,,https://openreview.net/forum?id=0XKvW4ijxp,/media/PosterPDFs/NeurIPS%202024/96926.png?t=1733319671.0065775
8,48,0.37225774,-0.11562894,1,0.4005834145426374,-0.08249288779183311,"[0.00016265974533816386, 0.9990332838149464, 5.6194716127027294e-21, 0.0008040564397153896, 8.529317010093416e-22]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0XeNkkENuI,The Road Less Scheduled,Stochastic Optimization;Optimization;Convex Optimization;Learning Rates;Learning Rate Schedules,7.5,3.5,Aaron Defazio;Xingyu Alice Yang;Ahmed Khaled;Konstantin Mishchenko;Harsh Mehta;Ashok Cutkosky,Meta;Meta;Princeton University;Samsung;Google Research;Boston University,Research Scientist;Research Engineer;PhD student;Researcher;Software Engineer;Assistant Professor,https://neurips.cc/virtual/2024/poster/96925,,,https://openreview.net/forum?id=0XeNkkENuI,/media/PosterPDFs/NeurIPS%202024/96925.png?t=1730837481.9895687
8,49,0.1460578,0.21914145,0,0.040549653809559626,0.01960725566245699,"[0.9768518034224011, 8.923725713351662e-07, 0.023131110365341014, 1.5119141319105024e-05, 1.0746983674668993e-06]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0ZZMUjZJYF,Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study,LLMs;Learning by Teaching;Reasoning;Mathematical Reasoning;Code Synthesis;Weak-to-Strong Generalization;In-Context Learning;Prompting;Knowledge Distillation;Education-Inspired,6.5,4.0,Xuefei Ning;Zifu Wang;Shiyao Li;Zinan Lin;Peiran Yao;Tianyu Fu;Matthew B. Blaschko;Guohao Dai;Huazhong Yang;Yu Wang,Tsinghua University;KU Leuven;Tsinghua University;Microsoft;Infinigence;Shanghai Jiaotong University;Tsinghua University;Tsinghua University;KU Leuven,Research Assistant Professor;PhD student;PhD student;Senior Researcher;Researcher;Associate Professor;Full Professor;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96924,,,https://openreview.net/forum?id=0ZZMUjZJYF,/media/PosterPDFs/NeurIPS%202024/96924.png?t=1732367562.4969194
8,50,0.07159563,-0.024327766,0,0.040549653809559626,0.01960725566245699,"[0.9432863055560579, 0.0008303621746772632, 1.3025192037289394e-09, 0.055850080005398164, 3.325096134755088e-05]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0ZeONp33f0,Graph Neural Networks and Arithmetic Circuits,Machine Learning;Graph Neural Networks;Arithmetic Circuits;Computational Complexity,6.5,3.25,Timon Barlag;Vivian Holzapfel;Laura Strieker;Jonni Virtema;Heribert Vollmer,Universität Hannover;Leibniz Universität Hannover;Leibniz Universität Hannover;University of Sheffield;Leibniz Universität Hannover,PhD student;Undergrad student;PhD student;Lecturer;Full Professor,https://neurips.cc/virtual/2024/poster/96923,,,https://openreview.net/forum?id=0ZeONp33f0,/media/PosterPDFs/NeurIPS%202024/96923.png?t=1732106485.9402945
8,51,-0.078428976,-0.18954016,3,-0.1122552559510126,-0.2630561550953563,"[0.18991290382433548, 0.0002021417498206665, 1.5999796580457879e-15, 0.8086518218693742, 0.001233132556468077]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,0aN7VWwp4g,Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting,Precipitation Nowcasting;Video Prediction;Fourier Analysis;Loss Function,6.0,4.0,Chiu-Wai Yan;Shi Quan Foo;Van-Hoan Trinh;Dit-Yan Yeung;Ka-Hing Wong;Wai-Kin Wong,Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology,Chair Professor;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96922,,,https://openreview.net/forum?id=0aN7VWwp4g,/media/PosterPDFs/NeurIPS%202024/96922.png?t=1731480203.951872
8,52,-0.23586994,0.37846398,2,-0.0929522627625797,0.3325470294663321,"[1.3058343987570682e-07, 3.472439536860772e-25, 0.9999863904886647, 6.689803159572871e-16, 1.3478927894652312e-05]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,0bFXbEMz8e,FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions,generative models;material generation;chemistry;flow matching;large language models,6.0,4.333333333333333,Anuroop Sriram;Benjamin Kurt Miller;Ricky T. Q. Chen;Brandon M Wood,"Meta Facebook;University of Amsterdam;FAIR at Meta;FAIR Labs, Meta AI",Principal Researcher;PhD student;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96921,,,https://openreview.net/forum?id=0bFXbEMz8e,/media/PosterPDFs/NeurIPS%202024/96921.png?t=1730973273.143089
8,53,-0.15925287,-0.015642455,4,-0.22277274633914645,0.00022583470936325936,"[0.15805776834615726, 3.5309852513001767e-09, 9.862347780222409e-07, 0.0031967943733404018, 0.8387444475147389]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,0bINeW40u4,Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning,Medical Multi-modal Alignment;Eye-gaze;Radiology,6.25,3.5,Chong Ma;Hanqi Jiang;Wenting Chen;Yiwei Li;Zihao Wu;Xiaowei Yu;Zhengliang Liu;Lei Guo;Dajiang Zhu;Tuo Zhang;Dinggang Shen;Tianming Liu;Xiang Li,"Northwest Polytechnical University Xi'an;Beijing Jiaotong University;City University of Hong Kong;University of Georgia;University of Georgia;University of Texas at Arlington, University of Texas at Arlington;University of Georgia;University of Texas at Arlington;Northwestern Polytechnical University;ShanghaiTech University;University of Georgia;Massachusetts General Hospital, Harvard University",PhD student;Undergrad student;PhD student;PhD student;PhD student;PhD student;PhD student;Assistant Professor;Associate Professor;Full Professor;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96920,,,https://openreview.net/forum?id=0bINeW40u4,
8,54,0.38273144,-0.19184409,1,0.4005834145426374,-0.08249288779183311,"[8.971946737615866e-06, 0.9996016456913742, 4.752164903497405e-26, 0.00038938236188817895, 2.0869792939101357e-24]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0cSQ1Sg7db,Generalization of Hamiltonian algorithms,Generalization;stochastic algorithms;concentration inequalities;PAC-Bayes,6.5,3.0,Andreas Maurer,,,https://neurips.cc/virtual/2024/poster/96919,,,https://openreview.net/forum?id=0cSQ1Sg7db,
8,55,-0.029614072,-0.05991212,0,0.040549653809559626,0.01960725566245699,"[0.8850360807874991, 4.110282778174039e-05, 1.0678001004007518e-09, 0.10653677769438653, 0.008386037622532696]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0cgDDa4OFr,Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation,source distribution estimation;maximum entropy;Sliced-Wasserstein distance;empirical Bayes;simulation-based inference,5.8,2.8,Julius Vetter;Guy Moss;Cornelius Schröder;Richard Gao;Jakob H. Macke,Eberhard-Karls-Universität Tübingen;Eberhard-Karls-Universität Tübingen;University Tübingen;Eberhard-Karls-Universität Tübingen,PhD student;PhD student;Postdoc;Postdoc,https://neurips.cc/virtual/2024/poster/96918,,,https://openreview.net/forum?id=0cgDDa4OFr,/media/PosterPDFs/NeurIPS%202024/96918.png?t=1733318904.6928847
8,56,-0.041920777,-0.1336057,3,-0.1122552559510126,-0.2630561550953563,"[0.49379749076130525, 0.00026688940868922783, 5.271628323254472e-13, 0.5038909558812298, 0.0020446639482485244]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,0d50Il6enG,Non-parametric classification via expand-and-sparsify representation,non-parametric regression;non-parametric classification;expand-and-sparsify representation;universal consistency;minimax-optimal convergence rate,6.0,3.0,Kaushik Sinha,Wichita State University,Associate Professor,https://neurips.cc/virtual/2024/poster/96917,,,https://openreview.net/forum?id=0d50Il6enG,/media/PosterPDFs/NeurIPS%202024/96917.png?t=1731697679.5420048
8,57,-0.05421332,-0.22073112,3,-0.1122552559510126,-0.2630561550953563,"[0.08727127349274567, 0.0008519296141224693, 8.806486918528957e-18, 0.911799793401798, 7.700349133396313e-05]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,0dtA21q83C,DeNetDM: Debiasing by Network Depth Modulation,Trustworthy Machine Learning;Debiasing;Robustness,6.0,3.5,Silpa Vadakkeeveetil Sreelatha;Adarsh Kappiyath;Abhra Chaudhuri;Anjan Dutta,University of Surrey;University of Exeter;University of Surrey,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96916,,,https://openreview.net/forum?id=0dtA21q83C,/media/PosterPDFs/NeurIPS%202024/96916.png?t=1733689557.490417
8,58,-0.19589648,0.09422963,4,-0.22277274633914645,0.00022583470936325936,"[0.017885158063331463, 4.983781314346454e-13, 0.0034543888523789305, 8.088219410767305e-06, 0.9786523648643803]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,0e5uOaJxo1,Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure,Graph Neural Network;Protein Sequence;Structure,5.0,3.3333333333333335,Bozhen Hu;Cheng Tan;Jun Xia;Yue Liu;Lirong Wu;Jiangbin Zheng;Yongjie Xu;Yufei Huang;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University, China;National University of Singapore;Westlake University;Westlake University;Westlake University;Zhejiang University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96915,,,https://openreview.net/forum?id=0e5uOaJxo1,/media/PosterPDFs/NeurIPS%202024/96915.png?t=1730385968.8958924
8,59,0.09615892,0.18102637,0,0.040549653809559626,0.01960725566245699,"[0.9917613151832723, 4.738056920409627e-07, 0.00814192620569274, 5.1936536607629315e-05, 4.4348268735304026e-05]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0feJEykDRx,Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models,spatial-temporal data mining;location-based service;check-in sequence;large language model,5.75,4.0,Letian Gong;Yan Lin;Xinyue Zhang;Yiwen Lu;Xuedi Han;Yichen Liu;Shengnan Guo;Youfang Lin;Huaiyu Wan,Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University,PhD student;PhD student;Undergrad student;Undergrad student;MS student;Associate Professor;Full Professor;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96914,,,https://openreview.net/forum?id=0feJEykDRx,/media/PosterPDFs/NeurIPS%202024/96914.png?t=1731289337.5941467
8,60,-0.013711061,-0.07216554,0,0.040549653809559626,0.01960725566245699,"[0.8413585961514445, 0.0001283869755819656, 1.8274515505365715e-10, 0.15583710674278145, 0.0026759099474469718]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0jld45XGgJ,Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?,neural collapse;deep neural collapse;unconstrained features model;deep unconstrained features model;low-rank bias,6.5,3.75,Peter Súkeník;Christoph H. Lampert;Marco Mondelli,Institute of Science and Technology;Institute of Science and Technology Austria;Institute of Science and Technology Austria,PhD student;Assistant Professor;Professor,https://neurips.cc/virtual/2024/poster/96913,,,https://openreview.net/forum?id=0jld45XGgJ,
8,61,0.49365819,-0.019841706,1,0.4005834145426374,-0.08249288779183311,"[3.342608150676065e-05, 0.9999444067799808, 1.0688979516325064e-18, 2.216713851256245e-05, 2.929709436249333e-28]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0l9yGPTHAU,Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms,Robust Markov decision process;norm;sample complexity;strong duality,6.5,3.0,Pierre Clavier;Laixi Shi;Erwan Le Pennec;Eric Mazumdar;Adam Wierman;Matthieu Geist,"École Polytechnique;California Institute of Technology;Ecole polytechnique;Deparment of Computing + Mathematical Sciences, California Institute of Technology;California Institute of Technology;Google",PhD student;Postdoc;Full Professor;Assistant Professor;Professor;Researcher,https://neurips.cc/virtual/2024/poster/96912,,,https://openreview.net/forum?id=0l9yGPTHAU,
8,62,-0.096782275,0.2680031,2,-0.0929522627625797,0.3325470294663321,"[0.0019653952045401526, 1.6667022476941294e-15, 0.9925898254951038, 1.5760666511346501e-09, 0.0054447777242877535]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,0lBx844upd,ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models,network pruning;unstructured pruning;large language model;ADMM;pre-conditioned conjugate gradient;optimization,5.333333333333333,3.0,Xiang Meng;Kayhan Behdin;Haoyue Wang;Rahul Mazumder,Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology,PhD student;PhD student;PhD student;Associate Professor,https://neurips.cc/virtual/2024/poster/96911,,,https://openreview.net/forum?id=0lBx844upd,/media/PosterPDFs/NeurIPS%202024/96911.png?t=1731079283.0533488
8,63,-0.07022652,-0.30347943,3,-0.1122552559510126,-0.2630561550953563,"[0.012938848043933485, 0.001491671651059905, 9.495505672595785e-23, 0.9855674108489558, 2.0694560508878e-06]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,0lau89u4oE,Accelerating Non-Maximum Suppression: A Graph Theory Perspective,non-maximum suppression;object detection;graph theory,5.5,3.25,King-Siong Si;Lu Sun;Weizhan Zhang;Tieliang Gong;Jiahao Wang;Jiang Liu;Hao Sun,Xi'an Jiaotong University;Xi'an Jiaotong University;North China University of Technology;China Telecom Corporation Ltd. Data&AI Technology Company,MS student;MS student;MS student;Researcher,https://neurips.cc/virtual/2024/poster/96910,,,https://openreview.net/forum?id=0lau89u4oE,/media/PosterPDFs/NeurIPS%202024/96910.png?t=1733315333.5240822
8,64,-0.08510746,-0.26066056,3,-0.1122552559510126,-0.2630561550953563,"[0.03696276021475815, 0.0004686941098837475, 9.542389289378167e-20, 0.9625233321915372, 4.521348382078075e-05]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,0m19blQT6y,BitsFusion: 1.99 bits Weight Quantization of Diffusion Model,Diffusion;Quantization;Stable Diffusion;Low bit,5.75,4.5,Yang Sui;Yanyu Li;Anil Kag;Yerlan Idelbayev;Junli Cao;Ju Hu;Dhritiman Sagar;Bo Yuan;Sergey Tulyakov;Jian Ren,Rutgers University;Northeastern University;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Rutgers University;Snap Inc.;Snap Inc.,PhD student;PhD student;Researcher;Researcher;Researcher;Researcher;Researcher;Assistant Professor;Director of Research;Research Scientist,https://neurips.cc/virtual/2024/poster/96909,,,https://openreview.net/forum?id=0m19blQT6y,/media/PosterPDFs/NeurIPS%202024/96909.png?t=1729915675.3170154
8,65,-0.00251228,0.3769304,2,-0.0929522627625797,0.3325470294663321,"[0.00020536952056564013, 9.288786454764965e-17, 0.9997916944027867, 2.333155514014581e-12, 2.9360743141657867e-06]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,0mRouJElbZ,ProgressGym: Alignment with a Millennium of Moral Progress,Progress Alignment;AI Alignment;Large Language Models,7.666666666666667,2.6666666666666665,Tianyi Qiu;Yang Zhang;Xuchuan Huang;Jasmine Xinze Li;Jiaming Ji;Yaodong Yang,"University of California, Berkeley;Peking University;Peking University;Peking University;Peking University;Peking University",Intern;Undergrad student;Undergrad student;Intern;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/97875,,,,/media/PosterPDFs/NeurIPS%202024/97875.png?t=1731742041.9348912
8,66,0.42614552,0.08994585,1,0.4005834145426374,-0.08249288779183311,"[0.024293766497307776, 0.9754532778773416, 5.547465528399001e-11, 0.00025295556987566816, 5.636159896449885e-21]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0nSY8NiILP,Tight Bounds for Learning RUMs from Small Slates,discrete choice;random utility model;approximation theory,6.0,2.75,Flavio Chierichetti;Mirko Giacchini;Ravi Kumar;Alessandro Panconesi;Andrew Tomkins,Sapienza University of Rome;Sapienza University of Rome;Google;Sapienza University of Rome;Google,Full Professor;PhD student;Research Scientist;Full Professor;Researcher,https://neurips.cc/virtual/2024/poster/96908,,,https://openreview.net/forum?id=0nSY8NiILP,/media/PosterPDFs/NeurIPS%202024/96908.png?t=1732698791.0319488
8,67,0.25132486,-0.20319358,1,0.4005834145426374,-0.08249288779183311,"[0.0009331433547556051, 0.9749441050521032, 4.578604744595778e-23, 0.024122751593140916, 2.1879910072133465e-16]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0nzKznCjFG,Private and Personalized Frequency Estimation in a Federated Setting,federated learning;personalization;privacy,5.75,3.0,Amrith Setlur;Vitaly Feldman;Kunal Talwar,Carnegie Mellon University;Apple AI Research;Apple,PhD student;Research Scientist;Research Scientist,https://neurips.cc/virtual/2024/poster/96907,,,https://openreview.net/forum?id=0nzKznCjFG,
8,68,-0.18157998,0.03947093,4,-0.22277274633914645,0.00022583470936325936,"[0.04396125833250996, 2.995269353519289e-11, 6.882105184384941e-05, 0.00013689418224786153, 0.9558330264034458]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,0o7Rd5jngV,Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling,Transformer;expressive power;theoretical insights,6.333333333333333,3.0,Mingze Wang;Weinan E,Peking University;Peking University,PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96906,,,https://openreview.net/forum?id=0o7Rd5jngV,
8,69,-0.12251995,-0.049827244,0,0.040549653809559626,0.01960725566245699,"[0.529242749809078, 2.7100910803773006e-07, 3.9251451928947095e-08, 0.034756321977738105, 0.43600061795262374]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0o9E8AsFgW,DarkSAM: Fooling Segment Anything Model to Segment Nothing,Segment Anything Model;Adversarial Example,6.333333333333333,4.0,Ziqi Zhou;Yufei Song;Minghui Li;Shengshan Hu;Xianlong Wang;Leo Yu Zhang;Dezhong Yao;Hai Jin,Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Griffith University;Huazhong University of Science and Technology;Huazhong University of Science and Technology,PhD student;PhD student;Assistant Professor;Associate Professor;PhD student;Researcher;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96905,,,https://openreview.net/forum?id=0o9E8AsFgW,
8,70,-0.18423451,0.25213403,2,-0.0929522627625797,0.3325470294663321,"[0.0002638708034176336, 6.3944970020476665e-18, 0.9832606190552425, 3.125552929746552e-10, 0.01647550982878463]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,0oUutV92YF,ProtGO: Function-Guided Protein Modeling for Unified Representation Learning,Teacher-student;Knowledge Distillation;Protein Function,5.666666666666667,3.6666666666666665,Bozhen Hu;Cheng Tan;Yongjie Xu;Zhangyang Gao;Jun Xia;Lirong Wu;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University;Westlake University, China;Westlake University, China;Westlake University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96904,,,https://openreview.net/forum?id=0oUutV92YF,/media/PosterPDFs/NeurIPS%202024/96904.png?t=1730386167.5899446
8,71,-0.04843812,0.4040603,2,-0.0929522627625797,0.3325470294663321,"[1.8878592202615865e-05, 2.1545672130403092e-19, 0.9999788142821299, 5.4000217332764945e-14, 2.3071256135422425e-06]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,0og7nmvDbe,Confidence Regulation Neurons in Language Models,LLMs;Interpretability;Mechanistic Interpretability,7.0,3.75,Alessandro Stolfo;Ben Peng Wu;Wes Gurnee;Yonatan Belinkov;Xingyi Song;Mrinmaya Sachan;Neel Nanda,"ETHZ - ETH Zurich;University of Sheffield;Massachusetts Institute of Technology;Technion, Technion;University of Sheffield;Google DeepMind;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Assistant Professor;Lecturer;Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96903,,,https://openreview.net/forum?id=0og7nmvDbe,
8,72,0.25011468,-0.18353273,1,0.4005834145426374,-0.08249288779183311,"[0.0018970779752846792, 0.969160188350221, 9.384259224421717e-22, 0.028942733674493345, 8.486433541484189e-16]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0qb8KoPsej,Accelerating Matroid Optimization through Fast Imprecise Oracles,matroid optimization;weak-strong models;learning-augmented algorithms;algorithms with predictions;query minimization;robustness,5.5,2.75,Franziska Eberle;Felix Hommelsheim;Alexander Lindermayr;Zhenwei Liu;Nicole Megow;Jens Schlöter,Technische Universität Berlin;Universität Bremen;Universität Bremen;Universität Bremen;Universität Bremen,Postdoc;Postdoc;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96902,,,https://openreview.net/forum?id=0qb8KoPsej,
8,73,0.24778247,-0.18444899,1,0.4005834145426374,-0.08249288779183311,"[0.002009838980161888, 0.9669795858670978, 9.562784718551565e-22, 0.0310105751527394, 1.1004047289857332e-15]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0rl5vWOzRU,Score-Optimal Diffusion Schedules,Diffusion model;adaptive schedule;Annealed Langevin,6.0,3.0,Christopher Williams;Andrew Campbell;Arnaud Doucet;Saifuddin Syed,University of Oxford;University of Oxford;University of Oxford;University of Oxford,PhD student;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96901,,,https://openreview.net/forum?id=0rl5vWOzRU,
8,74,-0.17648138,-0.41862112,3,-0.1122552559510126,-0.2630561550953563,"[0.0014218942371092243, 0.00017033209401242535, 1.0923666065848341e-28, 0.9984075264232967, 2.472455815139411e-07]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,0sJBW05a2W,3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration,Point Cloud Registration;Focus and Matching,5.666666666666667,4.333333333333333,Liyuan Zhang;Le Hui;qi liu;Bo Li;Yuchao Dai,Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwestern Polytechnical University Xi'an;Northwestern Polytechnical University,MS student;Associate Professor;Researcher;Associate Professor;Professor,https://neurips.cc/virtual/2024/poster/96900,,,https://openreview.net/forum?id=0sJBW05a2W,/media/PosterPDFs/NeurIPS%202024/96900.png?t=1731333373.8074756
8,75,-0.16704087,-0.3598848,3,-0.1122552559510126,-0.2630561550953563,"[0.004726850586279251, 9.3702389161641e-05, 8.070220139272016e-25, 0.9951739353484107, 5.511676148480039e-06]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,0sycTGl4In,4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization,Dynamic Novel View Synthesis;4D Gaussian splatting;Sparse reconstruction;in-the-wild,5.333333333333333,4.666666666666667,Mijeong Kim;Jongwoo Lim;Bohyung Han,Seoul National University;Seoul National University,Full Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96899,,,https://openreview.net/forum?id=0sycTGl4In,/media/PosterPDFs/NeurIPS%202024/96899.png?t=1733712090.5881364
8,76,0.61073065,0.018717432,1,0.4005834145426374,-0.08249288779183311,"[1.1580649080224594e-06, 0.9999982576800551, 1.2334235929648992e-19, 5.84255036961096e-07, 9.621886062600407e-37]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,0uGlKYS7a2,Maximizing utility in multi-agent environments by anticipating the behavior of other learners,Game Theory; no regret; learning theory;,5.5,3.25,Angelos Assos;Yuval Dagan;Constantinos Costis Daskalakis,Massachusetts Institute of Technology;Massachusetts Institute of Technology,MS student;Full Professor,https://neurips.cc/virtual/2024/poster/96898,,,https://openreview.net/forum?id=0uGlKYS7a2,/media/PosterPDFs/NeurIPS%202024/96898.png?t=1731753379.9098587
8,77,-0.07488669,0.3827278,2,-0.0929522627625797,0.3325470294663321,"[1.9149806423630983e-05, 1.6619531651607499e-19, 0.9999707492280192, 1.2836455958687032e-13, 1.0100965428655292e-05]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,0uXtFk5KNJ,BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models,block coordinate descent;large language models,5.25,3.75,Qijun Luo;Hengxu Yu;Xiao Li,"The Chinese University of Hong Kong, Shenzhen;The Chinese University of Hong Kong, Shenzhen;Chinese University of Hong Kong Shen Zhen",PhD student;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96897,,,https://openreview.net/forum?id=0uXtFk5KNJ,/media/PosterPDFs/NeurIPS%202024/96897.png?t=1733743857.9232197
8,78,0.022653038,0.24370801,2,-0.0929522627625797,0.3325470294663321,"[0.22807138737406185, 2.0357157631472783e-10, 0.7704806011650281, 7.55523097143805e-07, 0.0014472557342412634]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,0zFVhMBZHJ,Mixture of Tokens: Continuous MoE through Cross-Example Aggregation,LLM;Mixture of Experts;MoE;conditional computation;fully-differentiable;language modeling,6.0,3.6666666666666665,Szymon Antoniak;Michał Krutul;Maciej Pióro;Jakub Krajewski;Jan Ludziejewski;Kamil Ciebiera;Krystian Król;Tomasz Odrzygóźdź;Marek Cygan;Sebastian Jaszczur,IDEAS NCBR Sp.;IDEAS NCBR Sp.;University of Warsaw;University of Warsaw;IDEAS NCBR Sp.;University of Warsaw;IDEAS NCBR;Nomagic;University of Warsaw,PhD student;Researcher;PhD student;PhD student;Intern;MS student;Postdoc;Founder / CTO;PhD student,https://neurips.cc/virtual/2024/poster/96896,,,https://openreview.net/forum?id=0zFVhMBZHJ,/media/PosterPDFs/NeurIPS%202024/96896.png?t=1730308223.324062
8,79,0.24368975,0.18879418,0,0.040549653809559626,0.01960725566245699,"[0.9993621799136824, 0.000292638536356314, 0.00025996344846396783, 8.521789824983135e-05, 2.0324739840601466e-10]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,0zWzJj6lO3,Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents,cooperative AI;AI safety;LLM agents;cognitive science;language model evaluation;dynamic evaluation;alignment;agency;evolving benchmarks;multi-agent interactions,5.75,3.5,Giorgio Piatti;Zhijing Jin;Max Kleiman-Weiner;Bernhard Schölkopf;Mrinmaya Sachan;Rada Mihalcea,Common Sense Machines;University of Michigan;Swiss Federal Institute of Technology,Principal Researcher;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96895,,,https://openreview.net/forum?id=0zWzJj6lO3,
8,80,-0.16938657,-0.05973538,4,-0.22277274633914645,0.00022583470936325936,"[0.2116066128110243, 2.0575627651378903e-08, 3.232552087410081e-08, 0.016703191581261365, 0.7716901427065659]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,0zfUiSX5si,AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases,De Novo Peptide sequencing;Proteomics;Mass Spectrum,5.333333333333333,3.0,Jun Xia;Shaorong Chen;Jingbo Zhou;Xiaojun Shan;Wenjie Du;Zhangyang Gao;Cheng Tan;Bozhen Hu;Jiangbin Zheng;Stan Z. Li,"Westlake University, China;Westlake University;Jilin University;University of Electronic Science and Technology of China;University of Science and Technology of China;Westlake University, China;Zhejiang University & Westlake University;Westlake University;Westlake University;Westlake University",PhD student;PhD student;Undergrad student;Undergrad student;Assistant Professor;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96894,,,https://openreview.net/forum?id=0zfUiSX5si,
8,81,-0.25151917,-0.28693447,3,-0.1122552559510126,-0.2630561550953563,"[0.028670647811219516, 1.0670945176802609e-06, 1.5707478378240383e-18, 0.9677689233772301, 0.0035593617170328333]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,105ZuvpdyW,SegVol: Universal and Interactive Volumetric Medical Image Segmentation,Volumetric Medical Image Segmentation;3D Segmentation Foundation Model;Universal and Interactive 3D Segmentation,7.666666666666667,4.333333333333333,Yuxin Du;Fan BAI;Tiejun Huang;Bo Zhao,Beijing Academy of Artificial Intelligence;The Chinese University of Hong Kong;Peking University;BAAI,Intern;PhD student;Full Professor;Principal Researcher,https://neurips.cc/virtual/2024/poster/96893,,,https://openreview.net/forum?id=105ZuvpdyW,/media/PosterPDFs/NeurIPS%202024/96893.png?t=1731410503.871179
8,82,0.04577409,-0.24324691,3,-0.1122552559510126,-0.2630561550953563,"[0.03455328359663103, 0.04491617930637599, 8.075980164301229e-21, 0.9205304878151315, 4.9281861519879544e-08]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,1067784F6e,Data Distribution Valuation,Data distribution valuation;Huber model;Maximum mean discrepancy,6.333333333333333,4.333333333333333,Xinyi Xu;Shuaiqi Wang;Chuan-Sheng Foo;Bryan Kian Hsiang Low;Giulia Fanti,"National University of Singapore;Carnegie Mellon University;Institute for Infocomm Research, A*STAR;National University of Singapore;Carnegie Mellon University",PhD student;PhD student;Principal Scientist;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96892,,,https://openreview.net/forum?id=1067784F6e,/media/PosterPDFs/NeurIPS%202024/96892.png?t=1731176029.7581189
8,83,-0.22563006,-0.049784996,4,-0.22277274633914645,0.00022583470936325936,"[0.04726176832846298, 2.364911942078561e-10, 1.436950929852141e-07, 0.0024223807738907167, 0.9503157069660623]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,12A1RT1L87,Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?,Dataset Condensation;Dataset Distillation,5.666666666666667,3.6666666666666665,Lingao Xiao;Yang He,"School of Computer Science and  Engineering, Nanyang Technological University;Institute of High Performance Computing, Singapore, A*STAR",Undergrad student;Researcher,https://neurips.cc/virtual/2024/poster/96891,,,https://openreview.net/forum?id=12A1RT1L87,/media/PosterPDFs/NeurIPS%202024/96891.png?t=1731138766.8349779
8,84,-0.20074943,0.040258985,4,-0.22277274633914645,0.00022583470936325936,"[0.025936371064420597, 6.997236848104022e-12, 8.568814432364767e-05, 7.522629401690077e-05, 0.9739027144902416]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,135eKqDoRR,Bayesian-guided Label Mapping for Visual Reprogramming,visual reprogramming;adversarial reprogramming;output label mapping;Bayesian probability,7.25,4.0,Chengyi Cai;Zesheng Ye;Lei Feng;Jianzhong Qi;Feng Liu,University of Melbourne;Singapore University of Technology and Design;University of Melbourne;University of Melbourne,PhD student;Assistant Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96890,,,https://openreview.net/forum?id=135eKqDoRR,
8,85,-0.1496939,0.30529067,2,-0.0929522627625797,0.3325470294663321,"[5.393664990481331e-05, 5.194510154453493e-19, 0.9989913287829393, 7.92841044426544e-12, 0.0009547345592276754]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,14hLJr6kZ3,Enhancing Domain Adaptation through Prompt Gradient Alignment,transfer learning; domain adaptation; prompt-tuning,6.25,3.25,Hoang Phan;Tung Lam Tran;Quyen Tran;Trung Le,VinAi Research;VinAI Research;Monash University;New York University,Research resident;Research Resident;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96889,,,https://openreview.net/forum?id=14hLJr6kZ3,/media/PosterPDFs/NeurIPS%202024/96889.png?t=1732036918.0147438
8,86,0.2630342,0.051892787,0,0.040549653809559626,0.01960725566245699,"[0.8485827332814535, 0.14031446465456157, 4.349529469993656e-09, 0.011102797704989571, 9.465832346629416e-12]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,15460JjocO,Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners,multi-agent;reinforcement learning;robustness;diversity;specialization,7.0,3.6666666666666665,Rujikorn Charakorn;Poramate Manoonpong;Nat Dilokthanakul,Sakana AI;Vidyasirimedhi Institute of Science and Technology;King Mongkut's Institute of Technology Ladkrabang,Intern;Full Professor;Lecturer,https://neurips.cc/virtual/2024/poster/96888,,,https://openreview.net/forum?id=15460JjocO,/media/PosterPDFs/NeurIPS%202024/96888.png?t=1731395258.7214391
8,87,0.61719507,-0.024593957,1,0.4005834145426374,-0.08249288779183311,"[2.263730740829896e-07, 0.9999992912253279, 3.5770161778707347e-22, 4.824015979240983e-07, 3.4569394556729744e-38]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,15Jm9v7wCo,No-Regret Learning for Fair Multi-Agent Social Welfare Optimization,Online Learning;Nash Social Welfare,5.666666666666667,3.3333333333333335,Mengxiao Zhang;Ramiro Deo-Campo Vuong;Haipeng Luo,University of Southern California;University of Southern California,Undergrad student;Associate Professor,https://neurips.cc/virtual/2024/poster/96887,,,https://openreview.net/forum?id=15Jm9v7wCo,
8,88,-0.14552048,-0.15470643,3,-0.1122552559510126,-0.2630561550953563,"[0.38492267092858284, 5.874213644350533e-06, 1.6444188042317404e-12, 0.5235552728906283, 0.09151618196550007]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,15PS30UOUp,Kuro Siwo: 33 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping,Synthetic Aperture Radar;SAR;Deep Learning;Remote Sensing;Floods;dataset,6.75,3.75,Nikolaos Ioannis Bountos;Maria Sdraka;Angelos Zavras;Andreas Karavias;Ilektra Karasante;Themistocles Herekakis;Angeliki Thanasou;Dimitrios Michail;Ioannis Papoutsis,National Observatory of Athens;National Observatory of Athens;Harokopio University;The Centre for Research & Technology;National Observatory of Athens ;National Observatoty of Athens;National Observatory of Athens;Harokopio University;National Technical University of Athens,PhD student;Researcher;PhD student;Researcher;Researcher;Researcher;Researcher;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97874,,,,
8,89,0.004352061,-0.07103703,0,0.040549653809559626,0.01960725566245699,"[0.8382674037781281, 0.0002661726154352277, 1.1276192842479587e-10, 0.16049934493848603, 0.0009670785551887164]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,164QnJsYjF,Dense Associative Memory Through the Lens of Random Features,Associative Memory;Kernels;Random Features;Hopfield Network,6.0,3.0,Benjamin Hoover;Duen Horng Chau;Hendrik Strobelt;Parikshit Ram;Dmitry Krotov,International Business Machines;International Business Machines;International Business Machines;Massachusetts Institute of Technology;Georgia Institute of Technology,AI Research Engineer;Principal Researcher;Principal Researcher;Researcher;Full Professor,https://neurips.cc/virtual/2024/poster/96886,,,https://openreview.net/forum?id=164QnJsYjF,/media/PosterPDFs/NeurIPS%202024/96886.png?t=1733846086.053208
8,90,-0.31772932,0.41427824,2,-0.0929522627625797,0.3325470294663321,"[2.181568402065231e-09, 1.1053440968302051e-29, 0.9999995359315796, 1.939095145478238e-18, 4.6188685196318967e-07]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,168NLzTpw8,Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation,Vision-Language;Region-Level Understanding;Multimodal Large Language Model,5.75,3.75,Yaoyuan Liang;Zhuojun Cai;Jian Xu;Guanbo Huang;Yiran Wang;Xiao Liang;Jiahao Liu;Ziran Li;Jingang Wang;Shao-Lun Huang,"Tsinghua Shenzhen International Graduate School, Tsinghua University;Microsoft;University of Electronic Science and Technology of China;Tsinghua University;Tsinghua University;Meituan;Meituan;Tsinghua University",PhD student;Intern;Undergrad student;MS student;MS student;Researcher;Researcher;Associate Professor,https://neurips.cc/virtual/2024/poster/96885,,,https://openreview.net/forum?id=168NLzTpw8,
8,91,-0.118134014,0.26676714,2,-0.0929522627625797,0.3325470294663321,"[0.0010607440781277547, 3.3269033747930165e-16, 0.9919684430179554, 8.363710266468629e-10, 0.0069708120675457475]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,181llen2gw,A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks,Vision-Language Model;Fairness;Debias,6.333333333333333,3.6666666666666665,Hoin Jung;Taeuk Jang;Xiaoqian Wang,Purdue University;Purdue University;Purdue University,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96884,,,https://openreview.net/forum?id=181llen2gw,/media/PosterPDFs/NeurIPS%202024/96884.png?t=1731379505.2628894
8,92,-0.19037005,0.30377576,2,-0.0929522627625797,0.3325470294663321,"[1.5195329948304961e-05, 2.0228848667421874e-20, 0.9990479898174158, 2.1348880740773246e-12, 0.0009368148505010669]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,18FGRNd0wZ,Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation,tokenization of crystals;language models;materials generation,6.0,3.5,Keqiang Yan;Xiner Li;Hongyi Ling;Kenna Ashen;Carl Edwards;Raymundo Arroyave;Marinka Zitnik;Heng Ji;Xiaofeng Qian;Xiaoning Qian;Shuiwang Ji,"Texas A&M University;Texas A&M University - College Station;Texas A&M University - College Station;Texas A&M University - College Station;Genentech;Texas A&M University Main Campus;Harvard University;University of Illinois, Urbana-Champaign;Texas A&M University;Texas A&M;Texas A&M University",PhD student;PhD student;PhD student;PhD student;Intern;Assistant Professor;Full Professor;Associate Professor;Full Professor;Professor,https://neurips.cc/virtual/2024/poster/96883,,,https://openreview.net/forum?id=18FGRNd0wZ,/media/PosterPDFs/NeurIPS%202024/96883.png?t=1733428872.6393995
8,93,-0.18803668,0.09546091,4,-0.22277274633914645,0.00022583470936325936,"[0.02194087513657179, 8.374133217814671e-13, 0.003526303952095353, 9.675263610404494e-06, 0.9745231456468851]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,18RdkSv9h9,FINALLY: fast and universal speech enhancement with studio-like quality,speech enhancement; generative models,6.5,4.75,Nicholas Babaev;Kirill Tamogashev;Azat Saginbaev;Ivan Shchekotov;Hanbin Bae;Hosang Sung;WonJun Lee;Hoon-Young Cho;Pavel Andreev,"Samsung;Skolkovo Institute of Science and Technology;Moscow Institute of Physics and Technology;Samsung;Samsung;Samsung;Higher School of Economics, Higher School of Economics",Researcher;MS student;MS student;Principal Researcher;Researcher;Vice President;MS student,https://neurips.cc/virtual/2024/poster/96882,,,https://openreview.net/forum?id=18RdkSv9h9,/media/PosterPDFs/NeurIPS%202024/96882.png?t=1731683595.700073
8,94,0.32727078,-0.11709024,1,0.4005834145426374,-0.08249288779183311,"[0.0009079317200211043, 0.9956032981274603, 8.521105946664005e-20, 0.0034887701525185906, 7.227313047460042e-19]","[0.016747273100641665, 0.012195325842546791]",0.18894414332091172,1ATLLgvURu,Learning-Augmented Priority Queues,learning-augmented algorithms;algorithms with predictions;priority queue;shortest paths;Dijkstra,5.75,4.25,Ziyad Benomar;Christian Coester,University of Oxford,Associate Professor,https://neurips.cc/virtual/2024/poster/96881,,,https://openreview.net/forum?id=1ATLLgvURu,
8,95,0.3095995,0.5030761,2,-0.0929522627625797,0.3325470294663321,"[0.007451374703521846, 4.776503443661257e-11, 0.992548625247293, 1.419983359867744e-12, 2.966497110354394e-16]","[0.018748884194264525, 0.005451341070140449]",0.18954473287496063,1BZKqZphsW,Risk-Averse Fine-tuning of Large Language Models,Risk Averse Reinforcement Learning;Large Language Model Finetuning,5.8,3.2,Sapana Chaudhary;Ujwal Dinesha;Dileep Kalathil;Srinivas Shakkottai,Texas A&M University;Texas A&M University - College Station;Texas A&M University;Texas A&M,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96880,,,https://openreview.net/forum?id=1BZKqZphsW,/media/PosterPDFs/NeurIPS%202024/96880.png?t=1733328781.5713553
8,96,-0.26364937,-0.38828564,3,-0.1122552559510126,-0.2630561550953563,"[0.003084437466219521, 3.7672868918357813e-06, 5.167916231367724e-25, 0.9968966743140808, 1.5120932807711449e-05]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,1CssOqRYyz,Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds,compression;point cloud;diffusion,4.0,4.0,Kai Liu;Kang You;Pan Gao,"Nanjing University of Aeronautics and Astronautics;Nanjing university;Nanjing University of Aeronautics and Astronautics, Tsinghua University",MS student;PhD student;Associate Professor,,,,,
8,97,-0.25224024,-0.31188005,3,-0.1122552559510126,-0.2630561550953563,"[0.016172431777346015, 1.5843992162455669e-06, 4.010760779243688e-20, 0.9829051587834382, 0.0009208250399995523]","[0.01658360378403587, 0.00939948677876349]",0.1971253698630419,1Du3mMP5YN,Learning to Shape In-distribution Feature Space for Out-of-distribution Detection,Out-of-distribution Detection,5.75,4.0,Yonggang Zhang;Jie Lu;Bo Peng;Zhen Fang;Yiu-ming Cheung,Hong Kong Baptist University;University of Technology Sydney;University of Technology Sydney,Postdoc;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96879,,,https://openreview.net/forum?id=1Du3mMP5YN,/media/PosterPDFs/NeurIPS%202024/96879.png?t=1731745181.7993424
8,98,-0.30068702,-0.14781809,4,-0.22277274633914645,0.00022583470936325936,"[0.07794033893613062, 1.0160669763920423e-09, 2.457159408265918e-10, 0.06476829434254094, 0.8572913654595454]","[0.004427721180475497, 0.00605833200652028]",0.20184237391510332,1ELFGSNBGC,Multiview Scene Graph,scene representation; spatial understanding; place recognition; object correspondence; scene graph,5.25,3.25,Juexiao Zhang;Gao Zhu;Sihang Li;Xinhao Liu;Haorui Song;Xinran Tang;Chen Feng,New York University;New York University;New York University;New York University;New York University;New York University;New York University,PhD student;MS student;PhD student;PhD student;MS student;MS student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96878,,,https://openreview.net/forum?id=1ELFGSNBGC,/media/PosterPDFs/NeurIPS%202024/96878.png?t=1731728482.5838113
8,99,-0.09486352,0.005280091,0,0.040549653809559626,0.01960725566245699,"[0.6157109111840974, 1.0111671713300119e-07, 2.6302351587354945e-06, 0.00756920334848453, 0.37671715411554213]","[0.01592259814405513, 0.012367955019299335]",0.2225433800259823,1F32iCJFfa,Schrodinger Bridge Flow for Unpaired Data Translation,unpaired data translation;diffusion models;Schrodinger bridge;bridge matching;stochastic interpolant;flow matching,6.5,4.0,Valentin De Bortoli;Iryna Korshunova;Andriy Mnih;Arnaud Doucet,University of Oxford;Google DeepMind;Google DeepMind;University of Oxford,Postdoc;Researcher;Research Scientist;Full Professor,https://neurips.cc/virtual/2024/poster/96877,,,https://openreview.net/forum?id=1F32iCJFfa,/media/PosterPDFs/NeurIPS%202024/96877.png?t=1731688420.732189
9,0,0.08799766,-0.06060414,0,0.05848115929280148,0.01166383457759367,"[0.9220667504254502, 0.012847553069314422, 2.2989488343768234e-11, 0.06445856612662317, 0.0006271303556228551]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,00Sx577BT3,The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning,numerical simulations;fluid-dynamics;partial differential equations;operator learning,6.666666666666667,3.6666666666666665,Ruben Ohana;Michael McCabe;Lucas Thibaut Meyer;Rudy Morel;Fruzsina Julia Agocs;Miguel Beneitez;Marsha Berger;Blakesley Burkhart;Stuart B. Dalziel;Drummond Buschman Fielding;Daniel Fortunato;Jared A. Goldberg;Keiya Hirashima;Yan-Fei Jiang;Rich Kerswell;Suryanarayana Maddu;Jonah M. Miller;Payel Mukhopadhyay;Stefan S. Nixon;Jeff Shen;Romain Watteaux;Bruno Régaldo-Saint Blancard;François Rozet;Liam Holden Parker;Miles Cranmer;Shirley Ho,"Flatiron Institute;University of Colorado, Boulder;INRIA;Flatiron Institute;Flatiron Institute;University of Cambridge;Flatiron Institute;Rutgers University;University of Cambridge;Simons Foundation;Flatiron Institute;Flatiron Institute;Simons Foundation;University of Cambridge;Flatiron Institute/Simons Foundation;Los Alamos National Laboratory;University of California, Berkeley;University of Cambridge;Princeton University;CEA;Flatiron Institute;Flatiron Institute;Flatiron Institute;University of Cambridge;Carnegie Mellon University;The University of Tokyo",Postdoc;PhD student;PhD student;Postdoc;Postdoc;Postdoc;Full Professor;Assistant Professor;Director of the GK Batchelor Laboratory;Postdoc;Researcher;Postdoc;Researcher;Full Professor;Postdoc;Researcher;Postdoc;PhD student;PhD student;Researcher;Postdoc;Intern;Researcher;Assistant Professor;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/97882,,,,
9,1,-0.08406016,0.2851326,2,-0.11681432644787078,0.3248438774830968,"[0.0021769871389246027, 1.9986569791501255e-14, 0.9949229769694313, 1.626391906785675e-11, 0.002900035875360219]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,00uVk06eVK,On the Noise Robustness of In-Context Learning for Text Generation,In-Context Learning;Large Language Models;Noise Robustness,6.333333333333333,3.0,Hongfu Gao;Feipeng Zhang;Wenyu Jiang;Jun Shu;Feng Zheng;Hongxin Wei,Xi'an Jiaotong University;Xi'an Jiaotong University;Nanjing University;Xi'an Jiaotong University;Southern University of Science and Technology;Southern University of Science and Technology,MS student;Full Professor;PhD student;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96962,,,https://openreview.net/forum?id=00uVk06eVK,/media/PosterPDFs/NeurIPS%202024/96962.png?t=1731587881.4159098
9,2,-0.16364236,-0.11411294,4,-0.20691720368450753,-0.004029014381643935,"[0.1749767174049001, 2.6347478969977545e-06, 1.49893446373477e-11, 0.0843311041606618, 0.7406895436715516]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,01I55gys19,Few-Class Arena: A Benchmark for Efficient Vision Model Selection and Dataset Difficulty,few-class;efficiency;neural network;convolutional neural network;transformer;dataset difficulty measurement;scaling law,5.0,3.3333333333333335,Bryan Bo Cao;Lawrence O'Gorman;Michael Coss;Shubham Jain,Nokia networks GmbH;State University of New York at Stony Brook,Intern;Assistant Professor,,,,,
9,3,0.07371062,-0.27021888,3,-0.13361257096747306,-0.27899371683895335,"[0.22748332959090992, 0.21026358203723353, 1.4403531502489444e-23, 0.5622515021296729, 1.5862421837019919e-06]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,01XV5Za56k,Testing Calibration in Nearly-Linear Time,Calibration;Property testing;Linear programming,6.25,3.25,Lunjia Hu;Arun Jambulapati;Kevin Tian;Chutong Yang,Stanford University;Stanford University;Stanford University;University of Texas at Austin,PhD student;PhD student;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96961,,,https://openreview.net/forum?id=01XV5Za56k,
9,4,-0.1284643,0.3103237,2,-0.11681432644787078,0.3248438774830968,"[0.0001653488535653953, 7.516822530297538e-17, 0.9988965537072421, 2.5062131278979387e-13, 0.0009380974389421321]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,01lhHg8H9p,GLBench: A Comprehensive Benchmark for Graph with Large Language Models,Graph learning;Large Language Model;Zero-Shot,6.75,4.0,Yuhan Li;Peisong Wang;Xiao Zhu;Aochuan Chen;Haiyun Jiang;Deng Cai;Victor Wai Kin Chan;Jia Li,"Hong Kong University of Science and Technology;Tsinghua University;Beijing University of Posts and Telecommunications;Hong Kong University of Science and Technology;Tencent AI Lab;Tencent AI Lab;Shenzhen International Graduate School, Tsinghua University;Hong Kong University of Science and Technology",PhD student;MS student;Undergrad student;PhD student;Researcher;Research Scientist;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97881,,,,/media/PosterPDFs/NeurIPS%202024/97881.png?t=1731478194.2539835
9,5,-0.23808402,0.26056772,2,-0.11681432644787078,0.3248438774830968,"[1.5595320239201096e-05, 3.3097601148395593e-18, 0.9897654543836842, 9.34100000123515e-13, 0.010218950295142465]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,01qa1ZJs65,Bridge the Modality and Capability Gaps in Vision-Language Model Selection,Vision-Language Model;Model Selection;Zero-Shot Image Classification,5.25,4.0,Chao Yi;Yuhang He;De-Chuan Zhan;Han-Jia Ye,Nanjing University;Nanjing University;Nanjing University;Nanjing University,MS student;Undergrad student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96960,,,https://openreview.net/forum?id=01qa1ZJs65,/media/PosterPDFs/NeurIPS%202024/96960.png?t=1731123927.9174762
9,6,-0.10493148,-0.30384988,3,-0.13361257096747306,-0.27899371683895335,"[0.173289040560288, 0.0008571298547752502, 4.771738118175834e-24, 0.8256252612364124, 0.00022856834852423918]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,01s5ODIHKd,FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space,deep watermarking;latent frequency optimization,5.5,3.75,YiYang Guo;Ruizhe Li;Mude Hui;Hanzhong Allan Guo;Chen Zhang;Chuangjian Cai;Le Wan;Shangfei Wang,"University of Science and Technology of China;University of California, Santa Cruz;Renmin University of China;Tsinghua University;University of Science and Technology of China;University of Science and Technology of China",MS student;PhD student;MS student;PhD student;Full Professor;PhD student,https://neurips.cc/virtual/2024/poster/96959,,,https://openreview.net/forum?id=01s5ODIHKd,/media/PosterPDFs/NeurIPS%202024/96959.png?t=1730176108.8718698
9,7,-0.295713,-0.42771262,3,-0.13361257096747306,-0.27899371683895335,"[0.05691896081758478, 7.255533302903092e-06, 6.036202650013846e-32, 0.9430560406500478, 1.774299906452854e-05]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,02CIZ8qeDc,PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection,3D anomaly detection;Zero-shot 3D anomaly detection,6.0,3.6666666666666665,Qihang Zhou;Jiangtao Yan;Shibo He;Wenchao Meng;Jiming Chen,Zhejiang University;Zhejiang University;Zhejiang University;Zhejiang University,PhD student;MS student;Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96958,,,https://openreview.net/forum?id=02CIZ8qeDc,/media/PosterPDFs/NeurIPS%202024/96958.png?t=1731476864.9817398
9,8,-0.3188932,-0.023905918,4,-0.20691720368450753,-0.004029014381643935,"[0.0004889871827666459, 5.173503112319385e-12, 2.187595821729278e-07, 5.406597626247827e-05, 0.9994567280762152]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,02HWT9c4Lp,Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion,Semantic Scene completion，Voxel Proposal，Knowledge Distillation,5.5,4.0,Lubo Wang;Di Lin;Kairui Yang;Ruonan Liu;Qing Guo;Wuyuan Xie;Miaohui Wang;Lingyu Liang;Yi Wang;Ping Li,"Tianjin University;Tianjin University;Tianjin University;Tianjin University; Agency for Science, Technology and Research (A*STAR));Department of Software Engineering, Shenzhen University;Shenzhen University;South China University of Technology;Shenzhen University;The Hong Kong Polytechnic University",MS student;Associate Professor;PhD student;Associate Professor;Researcher;Associate Professor;Associate Professor;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96957,,,https://openreview.net/forum?id=02HWT9c4Lp,/media/PosterPDFs/NeurIPS%202024/96957.png?t=1731159292.6143699
9,9,0.52375084,0.03593809,1,0.39400268802779437,-0.08268788259142047,"[8.50762867173252e-06, 0.9999908654935773, 1.659639297045367e-17, 6.268777511066913e-07, 4.1556003502242477e-20]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,02r24A8doi,Achieving Constant Regret in Linear Markov Decision Processes,Reinforcement learning;Constant regret;Misspecified linear MDP,5.25,2.75,Weitong Zhang;Zhiyuan Fan;Jiafan He;Quanquan Gu,"Massachusetts Institute of Technology;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles",PhD student;PhD student;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96956,,,https://openreview.net/forum?id=02r24A8doi,
9,10,-0.24769914,0.06194072,4,-0.20691720368450753,-0.004029014381643935,"[0.000990641909908706, 2.6029215009903384e-12, 0.00016071378782466953, 2.318320832167886e-06, 0.9988463259788314]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,04EC4ZnZJj,MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers,transformer architecture;large language model;computational complexity reduction,6.0,3.5,Ning Ding;Yehui Tang;Haochen Qin;Zhenli Zhou;Chao Xu;Lin Li;Kai Han;Liao Heng;Yunhe Wang,"Peking University;Huawei Technologies Ltd.;Huawei Technologies Ltd.;Peking University;Peking University;Huawei Noah's Ark Lab;, Tsinghua University;Huawei Noah's Ark Lab",PhD student;Researcher;Researcher;MS student;Full Professor;Principal Researcher;Principal Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96955,,,https://openreview.net/forum?id=04EC4ZnZJj,
9,11,0.45866024,0.07679337,1,0.39400268802779437,-0.08268788259142047,"[0.0008557311331746949, 0.9991382349036221, 1.7257275048487798e-13, 6.033963030165458e-06, 3.94681763139294e-16]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,06JRFVK88O,Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games,Multi-agent Reinforcement Learning;Imitation Learning,6.666666666666667,3.0,The Viet Bui;Tien Anh Mai;Thanh Hong Nguyen,Singapore Management University;University of Oregon;Singapore Management University,Assistant Professor;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96954,,,https://openreview.net/forum?id=06JRFVK88O,/media/PosterPDFs/NeurIPS%202024/96954.png?t=1731744891.8886228
9,12,-0.21952832,-0.2596673,3,-0.13361257096747306,-0.27899371683895335,"[0.11367534724532442, 1.0898585666497399e-05, 7.752907557702461e-20, 0.8638773534019887, 0.02243640076702047]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,06Vt6f2js7,SyncTweedies: A General Generative Framework Based on Synchronized Diffusions,Diffusion Models;Synchronization;Texturing;3D Gaussian Splatting;Mesh;Panorama,6.666666666666667,3.6666666666666665,Jaihoon Kim;Juil Koo;Kyeongmin Yeo;Minhyuk Sung,KAIST;Adobe Systems;Korea Advanced Institute of Science & Technology;Korea Advanced Institute of Science & Technology,MS student;Intern;Undergrad student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96953,,,https://openreview.net/forum?id=06Vt6f2js7,
9,13,0.5387558,-0.021885695,1,0.39400268802779437,-0.08268788259142047,"[6.911058487618934e-07, 0.9999989049401706, 7.73393346633844e-21, 4.0395398077491767e-07, 1.105066070398506e-21]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,07N0qoaZ2L,Improved Analysis for Bandit Learning in Matching Markets,Bandits;Matching markets;Stable matching;Stable regret;Exploration and exploitation;$\alpha$-condition,5.5,3.0,Fang Kong;Zilong Wang;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;John Hopcroft Center, Shanghai Jiao Tong University",PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96952,,,https://openreview.net/forum?id=07N0qoaZ2L,/media/PosterPDFs/NeurIPS%202024/96952.png?t=1731746661.9360106
9,14,-0.31746334,-0.03755091,4,-0.20691720368450753,-0.004029014381643935,"[0.00065658445723002, 1.1770388946840568e-11, 6.324521256813175e-08, 0.00011297806071676056, 0.9992303742250702]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,08A6X7FSTs,Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text,Text-to-3D Scene Generation;Latent Diffusion Models,5.5,4.5,Xinyang Li;Zhangyu Lai;Linning Xu;Yansong Qu;Liujuan Cao;Shengchuan Zhang;Bo Dai;Rongrong Ji,Xiamen University;Xiamen University;Xiamen University;Xiamen University;Xiamen University;Shanghai AI Laboratory;Xiamen University;The Chinese University of Hong Kong,PhD student;MS student;PhD student;Full Professor;Assistant Professor;Scientist;Full Professor;Ph.D. student,https://neurips.cc/virtual/2024/poster/96951,,,https://openreview.net/forum?id=08A6X7FSTs,/media/PosterPDFs/NeurIPS%202024/96951.png?t=1732593534.8700738
9,15,0.21572201,0.15297481,0,0.05848115929280148,0.01166383457759367,"[0.9990891369431258, 0.0008537220252678356, 2.7228345832529888e-05, 2.820152672400514e-05, 1.7111590498391458e-06]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,08GbdALmEs,Learning Versatile Skills with Curriculum Masking,reinforcement learning;unsupervised pretraining;masked prediction;curriculum learning,5.25,3.25,Yao Tang;Zhihui Xie;Zichuan Lin;Deheng Ye;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;Tencent AI Lab;Tencent;John Hopcroft Center, Shanghai Jiao Tong University",Undergrad student;MS student;Researcher;Principal Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96950,,,https://openreview.net/forum?id=08GbdALmEs,/media/PosterPDFs/NeurIPS%202024/96950.png?t=1733319308.3295946
9,16,-0.17784788,-0.16018736,4,-0.20691720368450753,-0.004029014381643935,"[0.23218190075896564, 7.967982989907654e-06, 8.221189273767935e-14, 0.32661605330379434, 0.44119407795416776]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,08nbMTxazb,Chicks4FreeID: A Benchmark Dataset for Chicken Re-Identification,animal re-identification;chicken re-identification;chicken dataset;re-identification dataset;benchmark dataset;closed-set re-identification;computer vision;chicken instance segmentation;poultry;livestock,4.75,4.0,Daria Kern;Tobias Schiele;Ulrich Klauck;Winfred Ingabire,Glasgow Caledonian University;Hochschule Aalen;Glasgow Caledonian University,PhD student;Full Professor;Lecturer,,,,,
9,17,0.12485067,-0.17534988,1,0.39400268802779437,-0.08268788259142047,"[0.3413055240552977, 0.3511595265019266, 3.924075103842446e-18, 0.30753069893336804, 4.250509407701021e-06]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,08oUnmtj8Q,FSEO: A Few-Shot Evolutionary Optimization Framework for Expensive Multi-Objective Optimization and Constrained Optimization,Expensive optimization;few-shot optimization;multi-objective optimization;constrained optimization;surrogate-assisted evolutionary optimization,4.5,3.5,Xunzhao Yu,,,,,,,
9,18,-0.045080878,-0.32160506,3,-0.13361257096747306,-0.27899371683895335,"[0.20556954806726926, 0.007848120018319216, 6.865623713994279e-26, 0.7865640350366778, 1.829687773365868e-05]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,09RKw0vXjR,Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations,feature selection;sparse coding;dictionary learning;compressed sensing;iterative hard thresholding;pruning method,5.75,3.0,Yasutoshi Ida;Sekitoshi Kanai;Atsutoshi Kumagai;Tomoharu Iwata;Yasuhiro Fujiwara,NTT;NTT;NTT;NTT;NTT,Researcher;Researcher;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96949,,,https://openreview.net/forum?id=09RKw0vXjR,/media/PosterPDFs/NeurIPS%202024/96949.png?t=1733375377.8112724
9,19,-0.29219365,-0.1354431,4,-0.20691720368450753,-0.004029014381643935,"[0.01226715641913352, 9.531800890350205e-09, 3.86550374873381e-12, 0.024722443940165265, 0.963010390105035]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,09nyBqSdUz,RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance,Consistent image generation;Diverse image generation;Improve temporal-consistency;Feature injection from multiple images,5.5,4.0,Jiaojiao Fan;Haotian Xue;Qinsheng Zhang;Yongxin Chen,Georgia Institute of Technology;Georgia Institute of Technology;Georgia Institute of Technology;NVIDIA,PhD student;PhD student;Associate Professor;Research Intern,https://neurips.cc/virtual/2024/poster/96948,,,https://openreview.net/forum?id=09nyBqSdUz,/media/PosterPDFs/NeurIPS%202024/96948.png?t=1731392354.7708242
9,20,0.22983314,0.005944166,0,0.05848115929280148,0.01166383457759367,"[0.6824686052581642, 0.30789487777982505, 2.235782744556033e-10, 0.009635893185775159, 6.235526571031624e-07]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0AumdfLzpK,A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations,Visual Reinforcement Learning;Generalization,6.0,4.0,Wonil Song;Hyesong Choi;Kwanghoon Sohn;Dongbo Min,Yonsei Univ.;Ewha Womans University;Yonsei University;Ewha Womans University,PhD student;PhD student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96947,,,https://openreview.net/forum?id=0AumdfLzpK,/media/PosterPDFs/NeurIPS%202024/96947.png?t=1732451612.1247888
9,21,-0.2313607,0.15489271,4,-0.20691720368450753,-0.004029014381643935,"[0.0009601435901246544, 6.195330292350605e-14, 0.11886125980907422, 2.4724400622200428e-08, 0.8801785718763386]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0AwMciNShl,"Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality",Human evaluation;text-to-video models,5.25,4.0,Tianle Zhang;Langtian Ma;Yuchen Yan;Yuchen Zhang;Yue Yang;Ziyao Guo;Wenqi Shao;Kai Wang;Yang You;Yu Qiao;Ping Luo;Kaipeng Zhang,University of Electronic Science and Technology of China;Southern University of Science and Technology;The University of Nottingham Ningbo China;University of Electronic Science and Technology of China;Xidian University;Shanghai AI Laboratory;National University of Singapore;National University of Singapore;Shanghai AI Laboratory;The University of Hong Kong;Shanghai Jiaotong University,Undergrad student;Undergrad student;Undergrad student;Undergrad student;MS student;Researcher;PhD student;Professor;Researcher;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96946,,,https://openreview.net/forum?id=0AwMciNShl,/media/PosterPDFs/NeurIPS%202024/96946.png?t=1729079669.652648
9,22,0.44196302,-0.22339565,1,0.39400268802779437,-0.08268788259142047,"[8.88104322335518e-07, 0.9999908617247871, 1.3728849542315977e-29, 8.250170890563377e-06, 7.622374400078105e-20]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0C3bLHwjsY,Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions,Online Matching;Competitive Analysis;Fairness Maximization,6.25,3.0,Will Ma;Pan Xu,Columbia University;New Jersey Institute of Technology,Assistant Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96945,,,https://openreview.net/forum?id=0C3bLHwjsY,/media/PosterPDFs/NeurIPS%202024/96945.png?t=1731641014.5806563
9,23,0.31953293,-0.23248373,1,0.39400268802779437,-0.08268788259142047,"[0.00015929045802393389, 0.9992269212301459, 8.987707609634553e-27, 0.0006137883118116418, 1.8329684160055706e-14]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0DE1dLMW2b,Quantum algorithm for large-scale market equilibrium computation,market equilibrium computation;quantum algorithm,6.0,2.75,Po-Wei Huang;Patrick Rebentrost,Centre for Quantum Technologies;National University of Singapore,Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96944,,,https://openreview.net/forum?id=0DE1dLMW2b,/media/PosterPDFs/NeurIPS%202024/96944.png?t=1731426989.5298698
9,24,0.0025802255,-0.08199731,0,0.05848115929280148,0.01166383457759367,"[0.8728183234322393, 0.0010758385352417814, 2.377560420411457e-11, 0.10821685241932112, 0.017888985589422236]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0EfUYVMrLv,Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment,non-stationary environments;continuous distribution shift;test-time adaptation;unlabeled data,6.666666666666667,4.0,Zhen-Yu Zhang;Zhiyu Xie;Huaxiu Yao;Masashi Sugiyama,"RIKEN;Stanford University;Department of Computer Science, University of North Carolina at Chapel Hill;The University of Tokyo",Postdoc;MS student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96943,,,https://openreview.net/forum?id=0EfUYVMrLv,/media/PosterPDFs/NeurIPS%202024/96943.png?t=1731687693.6296034
9,25,0.023439856,-0.079839304,0,0.05848115929280148,0.01166383457759367,"[0.8877515485299707, 0.0021237954860585336, 1.690682674202385e-11, 0.1022392782287467, 0.00788537773831703]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0G0VpMjKyV,Sketching for Distributed Deep Learning: A Sharper Analysis,sketching;distributed learning;federated learning;optimization,5.666666666666667,4.0,Mayank Shrivastava;Berivan Isik;Qiaobo Li;Sanmi Koyejo;Arindam Banerjee,"University of Illinois, Urbana Champaign;Stanford University;Department of Computer Science, University of Illinois at Urbana-Champaign;University of Illinois, Urbana Champaign;Google",MS student;PhD student;PhD student;Professor;Research Scientist,https://neurips.cc/virtual/2024/poster/96942,,,https://openreview.net/forum?id=0G0VpMjKyV,/media/PosterPDFs/NeurIPS%202024/96942.png?t=1733481266.9121125
9,26,-0.06371302,0.3954228,2,-0.11681432644787078,0.3248438774830968,"[0.0003015545384752823, 7.705162423662781e-18, 0.9996822243166953, 9.21137904989559e-16, 1.6221144828531074e-05]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,0G5OK5vmmg,WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts,Benchmark;Large Language Models;Classical Chinese Literature and Language Arts,6.25,2.75,Jiahuan Cao;Yang Liu;Yongxin Shi;Kai Ding;Lianwen Jin,South China University of Technology;South China University of Technology;South China University of Technology;INTSIG Information;South China University of Technology,MS student;MS student;PhD student;Researcher;Professor,https://neurips.cc/virtual/2024/poster/97880,,,,/media/PosterPDFs/NeurIPS%202024/97880.png?t=1730896668.2191207
9,27,-0.2963673,0.015343715,4,-0.20691720368450753,-0.004029014381643935,"[0.0004474028162477278, 1.968213214413829e-12, 5.227177029439139e-06, 9.88024394530619e-06, 0.9995374897608094]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0G8AXwtmy2,T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition,harmful dataset;harmful content detection;Vision Language Model,6.5,3.75,Chen Yeh;You-Ming Chang;Wei-Chen Chiu;Ning Yu,National Yang Ming Chiao Tung University;National Yang Ming Chiao Tung University;National Chiao Tung University,MS student;MS student;Associate Professor,https://neurips.cc/virtual/2024/poster/97879,,,,/media/PosterPDFs/NeurIPS%202024/97879.png?t=1730218737.4487233
9,28,0.08612508,0.3898904,2,-0.11681432644787078,0.3248438774830968,"[0.09691040497782007, 1.2648942635773566e-12, 0.903086403782842, 5.934508972604007e-13, 3.1912374796458628e-06]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,0Gl5WxY6es,Grounding Multimodal Large Language Models in Actions,Embodied AI;Multimodal Large Language Models;Reinforcement Learning;Imitation Learning,6.0,3.6666666666666665,Andrew Szot;Bogdan Mazoure;Harsh Agrawal;R Devon Hjelm;Zsolt Kira;Alexander T Toshev,Georgia Institute of Technology;Apple;Apple;Apple;Georgia Institute of Technology;Apple,PhD student;Research Scientist;Researcher;Researcher;Assistant Professor;research scientist,https://neurips.cc/virtual/2024/poster/96941,,,https://openreview.net/forum?id=0Gl5WxY6es,
9,29,-0.20296153,0.2345368,2,-0.11681432644787078,0.3248438774830968,"[0.00020373852308503353, 5.456347217127174e-16, 0.9487143526875785, 5.119956650235993e-11, 0.05108190873813631]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,0Gmi8TkUC7,GenAI Arena: An Open Evaluation Platform for Generative Models,Evaluation;Benchmark;Platform;Generative Model,6.0,3.5,Dongfu Jiang;Max Ku;Tianle Li;Yuansheng Ni;Shizhuo Sun;Rongqi Fan;Wenhu Chen,Allen Institute for Artificial Intelligence;University of Waterloo;University of Waterloo;University of Toronto;NVIDIA;University of Waterloo,Intern;MS student;MS student;Undergrad student;Intern;Assistant Professor,https://neurips.cc/virtual/2024/poster/97878,,,,/media/PosterPDFs/NeurIPS%202024/97878.png?t=1730329031.3167162
9,30,-0.3021013,-0.23802479,3,-0.13361257096747306,-0.27899371683895335,"[0.059856491815821096, 4.494771934807186e-07, 1.260350785152717e-17, 0.7568879815424105, 0.18325507716457481]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,0HRRNEAQFp,A General Protocol to Probe Large Vision Models for 3D Physical Understanding,3D physical scene understanding; Representation probing protocol; Benchmark and evaluation,6.333333333333333,4.0,Guanqi Zhan;Chuanxia Zheng;Weidi Xie;Andrew Zisserman,University of Oxford;University of Oxford;Shanghai Jiaotong University,PhD student;Postdoc;Associate Professor,https://neurips.cc/virtual/2024/poster/96940,,,https://openreview.net/forum?id=0HRRNEAQFp,/media/PosterPDFs/NeurIPS%202024/96940.png?t=1731705235.0575316
9,31,0.40233114,0.06031101,1,0.39400268802779437,-0.08268788259142047,"[0.006929361636469173, 0.9930198094774065, 1.8600529048291632e-12, 5.082888409832145e-05, 1.6576887995742103e-13]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0JSKjdePGq,When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL,reinforcement learning;continuous-time,6.75,3.25,Lenart Treven;Bhavya Sukhija;Yarden As;Florian Dorfler;Andreas Krause,"Swiss Federal Institute of Technology;ETHZ - ETH Zurich;Department of Computer Science, ETHZ - ETH Zurich;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96939,,,https://openreview.net/forum?id=0JSKjdePGq,/media/PosterPDFs/NeurIPS%202024/96939.png?t=1730197260.75527
9,32,-0.31179968,-0.050893012,4,-0.20691720368450753,-0.004029014381643935,"[0.0009840891920304682, 3.259044063410622e-11, 1.7601623472777796e-08, 0.00024630071403887953, 0.9987695924597167]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0KseSacluJ,CoFie: Learning Compact Neural Surface Representations with Coordinate Fields,Neural Surface Representation;Shape Auto-Decoding;Coordinate Field.,5.0,4.0,Hanwen Jiang;Haitao Yang;Georgios Pavlakos;Qixing Huang,University of Texas at Austin;The University of Texas at Austin;University of Texas at Austin;University of Texas at Austin,PhD student;PhD student;Assistant Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96938,,,https://openreview.net/forum?id=0KseSacluJ,
9,33,0.11298243,0.035079706,0,0.05848115929280148,0.01166383457759367,"[0.994840624830039, 0.0014928622895259496, 1.2127306088143647e-07, 0.003145938943313664, 0.0005204526640608161]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0KvYLaTBTE,Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference,Generative models;Reinforcement learning;Decision transformer,6.333333333333333,3.0,Deqian Kong;Dehong Xu;Minglu Zhao;Bo Pang;Jianwen Xie;Andrew Lizarraga;Yuhao Huang;Sirui Xie;Ying Nian Wu,"University of California, Los Angeles;Amazon;University of California, Los Angeles;University of California, Los Angeles;Xi'an Jiaotong University;University of California, Los Angeles;University of California, Los Angeles;UCLA",PhD student;Intern;PhD student;PhD student;PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96937,,,https://openreview.net/forum?id=0KvYLaTBTE,
9,34,-0.23456638,0.06657637,4,-0.20691720368450753,-0.004029014381643935,"[0.0014063535951240878, 4.4641886012891474e-12, 0.00021486080770003979, 2.4758407810644314e-06, 0.9983763097519305]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0LXotew9Du,KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization,Quantization;KV Cache;LLM Inference;Compression;Long Context Length,6.25,3.25,Coleman Richard Charles Hooper;Sehoon Kim;Hiva Mohammadzadeh;Michael W. Mahoney;Sophia Shao;Kurt Keutzer;Amir Gholami,"University of California, Berkeley;University of California, Berkeley;University of California, Berkeley;University of California, Berkeley",PhD student;PhD student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96936,,,https://openreview.net/forum?id=0LXotew9Du,
9,35,0.11017645,-0.16371755,0,0.05848115929280148,0.01166383457759367,"[0.45562956657349124, 0.21186654400743235, 3.4264318482890755e-17, 0.33248895691901315, 1.4932500063025536e-05]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0Lb8vZT1DB,Reliable Learning of Halfspaces under Gaussian Marginals,reliable learning;agnostic learning;halfspace;proper leaning;statistical query,7.25,2.25,Ilias Diakonikolas;Lisheng Ren;Nikos Zarifis,"University of Wisconsin - Madison;University of Wisconsin - Madison;University of Wisconsin, Madison",Full Professor;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96935,,,https://openreview.net/forum?id=0Lb8vZT1DB,
9,36,0.1429859,0.059452157,0,0.05848115929280148,0.01166383457759367,"[0.9965879534958755, 0.00195766807424138, 3.748180517334531e-07, 0.0013306103576318572, 0.0001233932541992588]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0LfgE6kvKZ,Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning,Federated Learning; Model Merging,5.0,3.6666666666666665,Minghui Chen;Meirui Jiang;Xin Zhang;Qi Dou;Zehua Wang;Xiaoxiao Li,"University of British Columbia;Meta Facebook;The Chinese University of Hong Kong;University of British Columbia;University of British Columbia;Department of Computer Science and Engineering, The Chinese University of Hong Kong",PhD student;Research Scientist;Assistant Professor;Researcher;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96934,,,https://openreview.net/forum?id=0LfgE6kvKZ,/media/PosterPDFs/NeurIPS%202024/96934.png?t=1731518093.5294044
9,37,-0.040502112,0.02318828,0,0.05848115929280148,0.01166383457759367,"[0.663541971318077, 5.690990087250439e-06, 3.177023020291821e-06, 0.003080154531684778, 0.3333690061371306]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0Lr9HQijA1,Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations,Imprecise Label Learning,5.75,3.0,Hao Chen;Ankit Shah;Jindong Wang;Ran Tao;Yidong Wang;Xiang Li;Xing Xie;Masashi Sugiyama;Rita Singh;Bhiksha Raj,"Carnegie Mellon University;Accenture;Microsoft Research;Peking University;Microsoft Research Asia;The University of Tokyo;School of Computer Science, Carnegie Mellon University;Mohamed bin Zayed University of Artificial Intelligence",PhD student;Principal Researcher;Researcher;PhD student;Senior Principal Researcher;Full Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96933,,,https://openreview.net/forum?id=0Lr9HQijA1,/media/PosterPDFs/NeurIPS%202024/96933.png?t=1731704880.9846606
9,38,-0.06471333,0.08954511,4,-0.20691720368450753,-0.004029014381643935,"[0.3332260527978819, 9.005584285764988e-08, 0.0009825427943559902, 0.0001067862833256798, 0.6656845280685936]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0MXzbAv8xy,GFT: Graph Foundation Model with Transferable Tree Vocabulary,Graph Foundation Model;Transferability;Computation Tree;Graph Neural Network,6.0,3.75,Zehong Wang;Zheyuan Zhang;Nitesh V Chawla;Chuxu Zhang;Yanfang Ye,University of Notre Dame;University of Notre Dame;University of Notre Dame;University of Notre Dame,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96932,,,https://openreview.net/forum?id=0MXzbAv8xy,
9,39,0.06407858,0.09707585,0,0.05848115929280148,0.01166383457759367,"[0.9930155693085999, 2.0507513664510807e-05, 7.748344453901152e-05, 0.00022282794848291744, 0.006663611784713703]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0NMzBwqaAJ,Not All Tokens Are What You Need for Pretraining,pre-training;next token prediction;data optimization;data selection,7.666666666666667,4.0,Zhenghao Lin;Zhibin Gou;Yeyun Gong;Xiao Liu;yelong shen;Ruochen Xu;Chen Lin;Yujiu Yang;Jian Jiao;Nan Duan;Weizhu Chen,Xiamen University;Microsoft;Microsoft Research Asia;Microsoft Research;Xiamen University;Tsinghua University;Microsoft;Microsoft Research Asia;Microsoft GenAI,MS student;Intern;Researcher;Researcher;Full Professor;Full Professor;Principal Researcher;Principal Researcher;Vice President,https://neurips.cc/virtual/2024/poster/96931,,,https://openreview.net/forum?id=0NMzBwqaAJ,/media/PosterPDFs/NeurIPS%202024/96931.png?t=1733724962.7310221
9,40,-0.021407472,0.09407413,0,0.05848115929280148,0.01166383457759367,"[0.7509024280798134, 7.610386928999562e-07, 0.0007458131346672987, 0.00018605294772275618, 0.24816494479910353]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0NQzQVu9tY,DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors,representation learning;offline reinforcement learning;behavioral cloning;visual distractor,7.0,3.0,Joseph Ortiz;Antoine Dedieu;Wolfgang Lehrach;J Swaroop Guntupalli;Carter Wendelken;Ahmad Humayun;Sivaramakrishnan Swaminathan;Guangyao Zhou;Miguel Lazaro-Gredilla;Kevin Patrick Murphy,Google DeepMind;Google DeepMind;Google Deepmind;Google DeepMind;Google;Google DeepMind;Google DeepMind;Google DeepMind;Google Deepmind;Google,Researcher;Researcher;Researcher;Researcher;Researcher;Researcher;Research Engineer;Research Scientist;Research Scientist;Principal Researcher,https://neurips.cc/virtual/2024/poster/97877,,,,/media/PosterPDFs/NeurIPS%202024/97877.png?t=1733266397.4133346
9,41,-0.056248758,0.025906589,0,0.05848115929280148,0.01166383457759367,"[0.5063345779069081, 2.2928514570404057e-06, 5.135598596573359e-06, 0.0021833470742697175, 0.49147464656876855]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0SMhqvgHST,EEVEE and GATE: Finding the right benchmarks and how to run them seamlessly,multi-modal;benchmarks;machine learning;model evaluation;benchmark frameworks,6.0,4.0,Antreas Antoniou;Eleni Triantafillou;Hugo Larochelle;Sebastien Montella;Fady Rezk;Kiyoon Kim;Linus Ericsson;Pavlos Vougiouklis;Justin Engelmann;Elliot J. Crowley;Srihari Humbarwadi;Yi Liu;Guang Yang;Jeff Z. Pan;Amos Storkey,"Google;Google;Huawei Technologies Ltd.;Samsung;Deargen;University of Edinburgh, University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh, University of Edinburgh;University of Edinburgh",Researcher;Research Scientist;Researcher;Intern;Researcher;Postdoc;Researcher;Assistant Professor;Researcher;Full Professor;Full Professor,,,,,
9,42,-0.15132618,0.02146309,4,-0.20691720368450753,-0.004029014381643935,"[0.03086988097947985, 7.454765717461691e-09, 4.600334545398565e-06, 0.0002143184562500726, 0.968911192774959]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0SRJBtTNhX,IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors,Graph Machine Learning;Graph Data Augmentation;Graph Neural Networks,5.5,4.0,Shenghe Zheng;Hongzhi Wang;Xianglong Liu,Harbin Institute of Technology;Harbin Institute of Technology;Harbin Institute of Technology,MS student;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96930,,,https://openreview.net/forum?id=0SRJBtTNhX,/media/PosterPDFs/NeurIPS%202024/96930.png?t=1732617637.3891017
9,43,-0.18518934,0.0027779788,4,-0.20691720368450753,-0.004029014381643935,"[0.012918410537029164, 2.2233951856697466e-09, 9.742634741051322e-07, 0.00021179566524685562, 0.9868688173108547]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0T8xRFrScB,Benchmarking Counterfactual Image Generation,benchmark;causal inference;counterfactual image generation,7.25,3.75,Thomas Melistas;Nikos Spyrou;Nefeli Gkouti;Pedro Sanchez;Athanasios Vlontzos;Yannis Panagakis;Giorgos Papanastasiou;Sotirios A. Tsaftaris,"University of Athens;University of Athens;University of Athens;University of Edinburgh, University of Edinburgh;Spotify;Pfizer;University of Edinburgh",PhD student;PhD student;PhD student;PhD student;Researcher;Principal Researcher;Professor in machine learning and computer vision,https://neurips.cc/virtual/2024/poster/97876,,,,/media/PosterPDFs/NeurIPS%202024/97876.png?t=1731712408.6398222
9,44,0.5118622,-0.024860546,1,0.39400268802779437,-0.08268788259142047,"[2.4015812560122847e-06, 0.9999965116005907, 3.817748811983856e-20, 1.0868181531592384e-06, 2.6959424030402917e-20]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0TUMAAb3of,Queueing Matching Bandits with Preference Feedback,Bandits;Queue;Preference Feedback,6.0,2.5,Jung-hun Kim;Min-hwan Oh,Seoul National University;Seoul National University,Assistant Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96929,,,https://openreview.net/forum?id=0TUMAAb3of,/media/PosterPDFs/NeurIPS%202024/96929.png?t=1733803835.532587
9,45,-0.0018669573,0.3644946,2,-0.11681432644787078,0.3248438774830968,"[0.005494987162104989, 1.0155667493172409e-14, 0.9944708167385138, 1.7501350364923862e-13, 3.419609919609438e-05]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,0VeSCjRDBy,Adversarial Moment-Matching Distillation of Large Language Models,Knowledge distillation;Large language models;Imitation learning;Moment-matching;Adversarial training,6.25,3.0,Chen Jia,,,https://neurips.cc/virtual/2024/poster/96928,,,https://openreview.net/forum?id=0VeSCjRDBy,/media/PosterPDFs/NeurIPS%202024/96928.png?t=1731660620.7591212
9,46,-0.24925767,0.015651966,4,-0.20691720368450753,-0.004029014381643935,"[0.0015905584533592674, 2.5694729901080686e-11, 3.725024987441134e-06, 2.4200346771900317e-05, 0.9983815161491866]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0WCFI2Qx85,ScaleKD: Strong Vision Transformers Could Be Excellent Teachers,knowledge distillation;model compression;training acceleration;vision transformer;convolutional neural network;multi-layer perception,6.25,4.5,Jiawei Fan;Chao Li;Xiaolong Liu;Anbang Yao,Intel Labs China;Intel;Intel,Research Intern;Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96927,,,https://openreview.net/forum?id=0WCFI2Qx85,/media/PosterPDFs/NeurIPS%202024/96927.png?t=1731695837.2500114
9,47,0.2804453,-0.1894261,1,0.39400268802779437,-0.08268788259142047,"[0.0016747480674813642, 0.9951329340316768, 7.265990605359451e-23, 0.0031923178956686626, 5.173292629110613e-12]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0XKvW4ijxp,Learning-Augmented Algorithms with Explicit Predictors,online algorithms;learning-augmented algorithms;scheduling;caching,6.0,4.0,Marek Elias;Haim Kaplan;Yishay Mansour;Shay Moran,"Bocconi University;Technion, Technion;School of Computer Science, Tel Aviv University",Assistant Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96926,,,https://openreview.net/forum?id=0XKvW4ijxp,/media/PosterPDFs/NeurIPS%202024/96926.png?t=1733319671.0065775
9,48,0.37225774,-0.11562894,1,0.39400268802779437,-0.08268788259142047,"[0.0001568784884347888, 0.9996825732327084, 6.345817139905007e-21, 0.00016054827884793874, 8.960081419080636e-15]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0XeNkkENuI,The Road Less Scheduled,Stochastic Optimization;Optimization;Convex Optimization;Learning Rates;Learning Rate Schedules,7.5,3.5,Aaron Defazio;Xingyu Alice Yang;Ahmed Khaled;Konstantin Mishchenko;Harsh Mehta;Ashok Cutkosky,Meta;Meta;Princeton University;Samsung;Google Research;Boston University,Research Scientist;Research Engineer;PhD student;Researcher;Software Engineer;Assistant Professor,https://neurips.cc/virtual/2024/poster/96925,,,https://openreview.net/forum?id=0XeNkkENuI,/media/PosterPDFs/NeurIPS%202024/96925.png?t=1730837481.9895687
9,49,0.1460578,0.21914145,0,0.05848115929280148,0.01166383457759367,"[0.9917945791105519, 2.0819535860392237e-06, 0.008159717414309544, 5.871153834046361e-07, 4.303440616898604e-05]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0ZZMUjZJYF,Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study,LLMs;Learning by Teaching;Reasoning;Mathematical Reasoning;Code Synthesis;Weak-to-Strong Generalization;In-Context Learning;Prompting;Knowledge Distillation;Education-Inspired,6.5,4.0,Xuefei Ning;Zifu Wang;Shiyao Li;Zinan Lin;Peiran Yao;Tianyu Fu;Matthew B. Blaschko;Guohao Dai;Huazhong Yang;Yu Wang,Tsinghua University;KU Leuven;Tsinghua University;Microsoft;Infinigence;Shanghai Jiaotong University;Tsinghua University;Tsinghua University;KU Leuven,Research Assistant Professor;PhD student;PhD student;Senior Researcher;Researcher;Associate Professor;Full Professor;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96924,,,https://openreview.net/forum?id=0ZZMUjZJYF,/media/PosterPDFs/NeurIPS%202024/96924.png?t=1732367562.4969194
9,50,0.07159563,-0.024327766,0,0.05848115929280148,0.01166383457759367,"[0.9727408336027639, 0.0023770802527718587, 1.6346764448786548e-09, 0.022600569243650028, 0.0022815152661377143]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0ZeONp33f0,Graph Neural Networks and Arithmetic Circuits,Machine Learning;Graph Neural Networks;Arithmetic Circuits;Computational Complexity,6.5,3.25,Timon Barlag;Vivian Holzapfel;Laura Strieker;Jonni Virtema;Heribert Vollmer,Universität Hannover;Leibniz Universität Hannover;Leibniz Universität Hannover;University of Sheffield;Leibniz Universität Hannover,PhD student;Undergrad student;PhD student;Lecturer;Full Professor,https://neurips.cc/virtual/2024/poster/96923,,,https://openreview.net/forum?id=0ZeONp33f0,/media/PosterPDFs/NeurIPS%202024/96923.png?t=1732106485.9402945
9,51,-0.078428976,-0.18954016,3,-0.13361257096747306,-0.27899371683895335,"[0.4077238202677378, 0.0005563393548506253, 1.544917464020463e-16, 0.5782454207464397, 0.01347441963097178]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,0aN7VWwp4g,Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting,Precipitation Nowcasting;Video Prediction;Fourier Analysis;Loss Function,6.0,4.0,Chiu-Wai Yan;Shi Quan Foo;Van-Hoan Trinh;Dit-Yan Yeung;Ka-Hing Wong;Wai-Kin Wong,Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology,Chair Professor;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96922,,,https://openreview.net/forum?id=0aN7VWwp4g,/media/PosterPDFs/NeurIPS%202024/96922.png?t=1731480203.951872
9,52,-0.23586994,0.37846398,2,-0.11681432644787078,0.3248438774830968,"[3.5444744277706383e-07, 6.712374583588619e-23, 0.9999668492904612, 5.874981969249117e-18, 3.2796262095961913e-05]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,0bFXbEMz8e,FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions,generative models;material generation;chemistry;flow matching;large language models,6.0,4.333333333333333,Anuroop Sriram;Benjamin Kurt Miller;Ricky T. Q. Chen;Brandon M Wood,"Meta Facebook;University of Amsterdam;FAIR at Meta;FAIR Labs, Meta AI",Principal Researcher;PhD student;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96921,,,https://openreview.net/forum?id=0bFXbEMz8e,/media/PosterPDFs/NeurIPS%202024/96921.png?t=1730973273.143089
9,53,-0.15925287,-0.015642455,4,-0.20691720368450753,-0.004029014381643935,"[0.03794924710730159, 2.8029954149808178e-08, 1.9057820451163323e-07, 0.0010374788085519388, 0.9610130554759878]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0bINeW40u4,Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning,Medical Multi-modal Alignment;Eye-gaze;Radiology,6.25,3.5,Chong Ma;Hanqi Jiang;Wenting Chen;Yiwei Li;Zihao Wu;Xiaowei Yu;Zhengliang Liu;Lei Guo;Dajiang Zhu;Tuo Zhang;Dinggang Shen;Tianming Liu;Xiang Li,"Northwest Polytechnical University Xi'an;Beijing Jiaotong University;City University of Hong Kong;University of Georgia;University of Georgia;University of Texas at Arlington, University of Texas at Arlington;University of Georgia;University of Texas at Arlington;Northwestern Polytechnical University;ShanghaiTech University;University of Georgia;Massachusetts General Hospital, Harvard University",PhD student;Undergrad student;PhD student;PhD student;PhD student;PhD student;PhD student;Assistant Professor;Associate Professor;Full Professor;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96920,,,https://openreview.net/forum?id=0bINeW40u4,
9,54,0.38273144,-0.19184409,1,0.39400268802779437,-0.08268788259142047,"[2.0798681032323095e-05, 0.9998973208572318, 6.859077351231199e-26, 8.188046173565647e-05, 1.5291476417376132e-16]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0cSQ1Sg7db,Generalization of Hamiltonian algorithms,Generalization;stochastic algorithms;concentration inequalities;PAC-Bayes,6.5,3.0,Andreas Maurer,,,https://neurips.cc/virtual/2024/poster/96919,,,https://openreview.net/forum?id=0cSQ1Sg7db,
9,55,-0.029614072,-0.05991212,0,0.05848115929280148,0.01166383457759367,"[0.8456441673464703, 0.00017841617329813892, 6.89905318263597e-10, 0.0599539474524726, 0.09422346833785371]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0cgDDa4OFr,Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation,source distribution estimation;maximum entropy;Sliced-Wasserstein distance;empirical Bayes;simulation-based inference,5.8,2.8,Julius Vetter;Guy Moss;Cornelius Schröder;Richard Gao;Jakob H. Macke,Eberhard-Karls-Universität Tübingen;Eberhard-Karls-Universität Tübingen;University Tübingen;Eberhard-Karls-Universität Tübingen,PhD student;PhD student;Postdoc;Postdoc,https://neurips.cc/virtual/2024/poster/96918,,,https://openreview.net/forum?id=0cgDDa4OFr,/media/PosterPDFs/NeurIPS%202024/96918.png?t=1733318904.6928847
9,56,-0.041920777,-0.1336057,0,0.05848115929280148,0.01166383457759367,"[0.668392378508564, 0.0007633158203633629, 1.4024281857165183e-13, 0.30411655023342393, 0.026727755437508435]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0d50Il6enG,Non-parametric classification via expand-and-sparsify representation,non-parametric regression;non-parametric classification;expand-and-sparsify representation;universal consistency;minimax-optimal convergence rate,6.0,3.0,Kaushik Sinha,Wichita State University,Associate Professor,https://neurips.cc/virtual/2024/poster/96917,,,https://openreview.net/forum?id=0d50Il6enG,/media/PosterPDFs/NeurIPS%202024/96917.png?t=1731697679.5420048
9,57,-0.05421332,-0.22073112,3,-0.13361257096747306,-0.27899371683895335,"[0.3325343710585491, 0.0018716203602159394, 8.088718495726436e-19, 0.6638263189400103, 0.0017676896412245327]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,0dtA21q83C,DeNetDM: Debiasing by Network Depth Modulation,Trustworthy Machine Learning;Debiasing;Robustness,6.0,3.5,Silpa Vadakkeeveetil Sreelatha;Adarsh Kappiyath;Abhra Chaudhuri;Anjan Dutta,University of Surrey;University of Exeter;University of Surrey,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96916,,,https://openreview.net/forum?id=0dtA21q83C,/media/PosterPDFs/NeurIPS%202024/96916.png?t=1733689557.490417
9,58,-0.19589648,0.09422963,4,-0.20691720368450753,-0.004029014381643935,"[0.003954220876354612, 1.2274739341269087e-11, 0.001538824888525986, 1.6316497003864224e-06, 0.9945053225731442]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0e5uOaJxo1,Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure,Graph Neural Network;Protein Sequence;Structure,5.0,3.3333333333333335,Bozhen Hu;Cheng Tan;Jun Xia;Yue Liu;Lirong Wu;Jiangbin Zheng;Yongjie Xu;Yufei Huang;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University, China;National University of Singapore;Westlake University;Westlake University;Westlake University;Zhejiang University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96915,,,https://openreview.net/forum?id=0e5uOaJxo1,/media/PosterPDFs/NeurIPS%202024/96915.png?t=1730385968.8958924
9,59,0.09615892,0.18102637,0,0.05848115929280148,0.01166383457759367,"[0.9928759178831775, 1.7361767558933371e-06, 0.006183156059846593, 3.982323978762963e-06, 0.0009352075562412174]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0feJEykDRx,Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models,spatial-temporal data mining;location-based service;check-in sequence;large language model,5.75,4.0,Letian Gong;Yan Lin;Xinyue Zhang;Yiwen Lu;Xuedi Han;Yichen Liu;Shengnan Guo;Youfang Lin;Huaiyu Wan,Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University,PhD student;PhD student;Undergrad student;Undergrad student;MS student;Associate Professor;Full Professor;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96914,,,https://openreview.net/forum?id=0feJEykDRx,/media/PosterPDFs/NeurIPS%202024/96914.png?t=1731289337.5941467
9,60,-0.013711061,-0.07216554,0,0.05848115929280148,0.01166383457759367,"[0.8729855405283693, 0.00045978681411880823, 1.1524669235631646e-10, 0.08497019697542749, 0.0415844755668375]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0jld45XGgJ,Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?,neural collapse;deep neural collapse;unconstrained features model;deep unconstrained features model;low-rank bias,6.5,3.75,Peter Súkeník;Christoph H. Lampert;Marco Mondelli,Institute of Science and Technology;Institute of Science and Technology Austria;Institute of Science and Technology Austria,PhD student;Assistant Professor;Professor,https://neurips.cc/virtual/2024/poster/96913,,,https://openreview.net/forum?id=0jld45XGgJ,
9,61,0.49365819,-0.019841706,1,0.39400268802779437,-0.08268788259142047,"[6.74603889849104e-06, 0.9999911449048013, 2.5748046516681526e-19, 2.1090563002238815e-06, 2.8340319833409e-19]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0l9yGPTHAU,Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms,Robust Markov decision process;norm;sample complexity;strong duality,6.5,3.0,Pierre Clavier;Laixi Shi;Erwan Le Pennec;Eric Mazumdar;Adam Wierman;Matthieu Geist,"École Polytechnique;California Institute of Technology;Ecole polytechnique;Deparment of Computing + Mathematical Sciences, California Institute of Technology;California Institute of Technology;Google",PhD student;Postdoc;Full Professor;Assistant Professor;Professor;Researcher,https://neurips.cc/virtual/2024/poster/96912,,,https://openreview.net/forum?id=0l9yGPTHAU,
9,62,-0.096782275,0.2680031,2,-0.11681432644787078,0.3248438774830968,"[0.0026135863488202364, 3.9705109863733674e-14, 0.9897374447157624, 5.960413362179487e-11, 0.00764896887577339]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,0lBx844upd,ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models,network pruning;unstructured pruning;large language model;ADMM;pre-conditioned conjugate gradient;optimization,5.333333333333333,3.0,Xiang Meng;Kayhan Behdin;Haoyue Wang;Rahul Mazumder,Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology,PhD student;PhD student;PhD student;Associate Professor,https://neurips.cc/virtual/2024/poster/96911,,,https://openreview.net/forum?id=0lBx844upd,/media/PosterPDFs/NeurIPS%202024/96911.png?t=1731079283.0533488
9,63,-0.07022652,-0.30347943,3,-0.13361257096747306,-0.27899371683895335,"[0.19779440543668045, 0.0027474799476899588, 2.3844117828659768e-24, 0.7993710582173981, 8.705639823161755e-05]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,0lau89u4oE,Accelerating Non-Maximum Suppression: A Graph Theory Perspective,non-maximum suppression;object detection;graph theory,5.5,3.25,King-Siong Si;Lu Sun;Weizhan Zhang;Tieliang Gong;Jiahao Wang;Jiang Liu;Hao Sun,Xi'an Jiaotong University;Xi'an Jiaotong University;North China University of Technology;China Telecom Corporation Ltd. Data&AI Technology Company,MS student;MS student;MS student;Researcher,https://neurips.cc/virtual/2024/poster/96910,,,https://openreview.net/forum?id=0lau89u4oE,/media/PosterPDFs/NeurIPS%202024/96910.png?t=1733315333.5240822
9,64,-0.08510746,-0.26066056,3,-0.13361257096747306,-0.27899371683895335,"[0.22876820739323744, 0.0010350307732217064, 3.3976172796937415e-21, 0.7693246271007296, 0.0008721347328112026]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,0m19blQT6y,BitsFusion: 1.99 bits Weight Quantization of Diffusion Model,Diffusion;Quantization;Stable Diffusion;Low bit,5.75,4.5,Yang Sui;Yanyu Li;Anil Kag;Yerlan Idelbayev;Junli Cao;Ju Hu;Dhritiman Sagar;Bo Yuan;Sergey Tulyakov;Jian Ren,Rutgers University;Northeastern University;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Rutgers University;Snap Inc.;Snap Inc.,PhD student;PhD student;Researcher;Researcher;Researcher;Researcher;Researcher;Assistant Professor;Director of Research;Research Scientist,https://neurips.cc/virtual/2024/poster/96909,,,https://openreview.net/forum?id=0m19blQT6y,/media/PosterPDFs/NeurIPS%202024/96909.png?t=1729915675.3170154
9,65,-0.00251228,0.3769304,2,-0.11681432644787078,0.3248438774830968,"[0.004334622307961337, 3.633676718799941e-15, 0.9956450005229478, 5.538014238582889e-14, 2.0377169031702946e-05]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,0mRouJElbZ,ProgressGym: Alignment with a Millennium of Moral Progress,Progress Alignment;AI Alignment;Large Language Models,7.666666666666667,2.6666666666666665,Tianyi Qiu;Yang Zhang;Xuchuan Huang;Jasmine Xinze Li;Jiaming Ji;Yaodong Yang,"University of California, Berkeley;Peking University;Peking University;Peking University;Peking University;Peking University",Intern;Undergrad student;Undergrad student;Intern;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/97875,,,,/media/PosterPDFs/NeurIPS%202024/97875.png?t=1731742041.9348912
9,66,0.42614552,0.08994585,1,0.39400268802779437,-0.08268788259142047,"[0.006612940838375872, 0.9933681518674942, 7.765972292369757e-12, 1.8907286336470177e-05, 2.7539911751828914e-14]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0nSY8NiILP,Tight Bounds for Learning RUMs from Small Slates,discrete choice;random utility model;approximation theory,6.0,2.75,Flavio Chierichetti;Mirko Giacchini;Ravi Kumar;Alessandro Panconesi;Andrew Tomkins,Sapienza University of Rome;Sapienza University of Rome;Google;Sapienza University of Rome;Google,Full Professor;PhD student;Research Scientist;Full Professor;Researcher,https://neurips.cc/virtual/2024/poster/96908,,,https://openreview.net/forum?id=0nSY8NiILP,/media/PosterPDFs/NeurIPS%202024/96908.png?t=1732698791.0319488
9,67,0.25132486,-0.20319358,1,0.39400268802779437,-0.08268788259142047,"[0.004210575902263589, 0.9875313803157817, 5.798670728903255e-23, 0.008258043736451975, 4.5502759772464076e-11]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0nzKznCjFG,Private and Personalized Frequency Estimation in a Federated Setting,federated learning;personalization;privacy,5.75,3.0,Amrith Setlur;Vitaly Feldman;Kunal Talwar,Carnegie Mellon University;Apple AI Research;Apple,PhD student;Research Scientist;Research Scientist,https://neurips.cc/virtual/2024/poster/96907,,,https://openreview.net/forum?id=0nzKznCjFG,
9,68,-0.18157998,0.03947093,4,-0.20691720368450753,-0.004029014381643935,"[0.009473831378116962, 4.4601031465832457e-10, 2.0749171024351054e-05, 3.779468219194126e-05, 0.9904676243226564]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0o7Rd5jngV,Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling,Transformer;expressive power;theoretical insights,6.333333333333333,3.0,Mingze Wang;Weinan E,Peking University;Peking University,PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96906,,,https://openreview.net/forum?id=0o7Rd5jngV,
9,69,-0.12251995,-0.049827244,4,-0.20691720368450753,-0.004029014381643935,"[0.18954491982633, 1.4024396606047487e-06, 7.953919308983362e-09, 0.013165218285681969, 0.7972884514944082]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0o9E8AsFgW,DarkSAM: Fooling Segment Anything Model to Segment Nothing,Segment Anything Model;Adversarial Example,6.333333333333333,4.0,Ziqi Zhou;Yufei Song;Minghui Li;Shengshan Hu;Xianlong Wang;Leo Yu Zhang;Dezhong Yao;Hai Jin,Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Griffith University;Huazhong University of Science and Technology;Huazhong University of Science and Technology,PhD student;PhD student;Assistant Professor;Associate Professor;PhD student;Researcher;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96905,,,https://openreview.net/forum?id=0o9E8AsFgW,
9,70,-0.18423451,0.25213403,2,-0.11681432644787078,0.3248438774830968,"[0.0001850608613917488, 3.485816421714732e-16, 0.9796955106373882, 1.461295486909163e-11, 0.02011942848660675]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,0oUutV92YF,ProtGO: Function-Guided Protein Modeling for Unified Representation Learning,Teacher-student;Knowledge Distillation;Protein Function,5.666666666666667,3.6666666666666665,Bozhen Hu;Cheng Tan;Yongjie Xu;Zhangyang Gao;Jun Xia;Lirong Wu;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University;Westlake University, China;Westlake University, China;Westlake University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96904,,,https://openreview.net/forum?id=0oUutV92YF,/media/PosterPDFs/NeurIPS%202024/96904.png?t=1730386167.5899446
9,71,-0.04843812,0.4040603,2,-0.11681432644787078,0.3248438774830968,"[0.00049879323135799, 1.2986819994704463e-17, 0.9994907715012101, 7.872433540149394e-16, 1.0435267430997738e-05]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,0og7nmvDbe,Confidence Regulation Neurons in Language Models,LLMs;Interpretability;Mechanistic Interpretability,7.0,3.75,Alessandro Stolfo;Ben Peng Wu;Wes Gurnee;Yonatan Belinkov;Xingyi Song;Mrinmaya Sachan;Neel Nanda,"ETHZ - ETH Zurich;University of Sheffield;Massachusetts Institute of Technology;Technion, Technion;University of Sheffield;Google DeepMind;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Assistant Professor;Lecturer;Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96903,,,https://openreview.net/forum?id=0og7nmvDbe,
9,72,0.25011468,-0.18353273,1,0.39400268802779437,-0.08268788259142047,"[0.006378983772407281, 0.9840152324822176, 1.1993838204754037e-21, 0.009605783626297538, 1.1907778530467732e-10]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0qb8KoPsej,Accelerating Matroid Optimization through Fast Imprecise Oracles,matroid optimization;weak-strong models;learning-augmented algorithms;algorithms with predictions;query minimization;robustness,5.5,2.75,Franziska Eberle;Felix Hommelsheim;Alexander Lindermayr;Zhenwei Liu;Nicole Megow;Jens Schlöter,Technische Universität Berlin;Universität Bremen;Universität Bremen;Universität Bremen;Universität Bremen,Postdoc;Postdoc;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96902,,,https://openreview.net/forum?id=0qb8KoPsej,
9,73,0.24778247,-0.18444899,1,0.39400268802779437,-0.08268788259142047,"[0.006874721110773149, 0.9827519846894945, 1.2123119315005603e-21, 0.010373294057351889, 1.423806580085769e-10]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0rl5vWOzRU,Score-Optimal Diffusion Schedules,Diffusion model;adaptive schedule;Annealed Langevin,6.0,3.0,Christopher Williams;Andrew Campbell;Arnaud Doucet;Saifuddin Syed,University of Oxford;University of Oxford;University of Oxford;University of Oxford,PhD student;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96901,,,https://openreview.net/forum?id=0rl5vWOzRU,
9,74,-0.17648138,-0.41862112,3,-0.13361257096747306,-0.27899371683895335,"[0.14430391360293776, 0.00032690453764472257, 4.3517131226515386e-32, 0.8553632819245495, 5.8999348680381985e-06]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,0sJBW05a2W,3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration,Point Cloud Registration;Focus and Matching,5.666666666666667,4.333333333333333,Liyuan Zhang;Le Hui;qi liu;Bo Li;Yuchao Dai,Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwestern Polytechnical University Xi'an;Northwestern Polytechnical University,MS student;Associate Professor;Researcher;Associate Professor;Professor,https://neurips.cc/virtual/2024/poster/96900,,,https://openreview.net/forum?id=0sJBW05a2W,/media/PosterPDFs/NeurIPS%202024/96900.png?t=1731333373.8074756
9,75,-0.16704087,-0.3598848,3,-0.13361257096747306,-0.27899371683895335,"[0.11981341930453024, 0.0002074418645825339, 1.2484945807183344e-27, 0.8799025347973476, 7.660403353979342e-05]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,0sycTGl4In,4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization,Dynamic Novel View Synthesis;4D Gaussian splatting;Sparse reconstruction;in-the-wild,5.333333333333333,4.666666666666667,Mijeong Kim;Jongwoo Lim;Bohyung Han,Seoul National University;Seoul National University,Full Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96899,,,https://openreview.net/forum?id=0sycTGl4In,/media/PosterPDFs/NeurIPS%202024/96899.png?t=1733712090.5881364
9,76,0.61073065,0.018717432,1,0.39400268802779437,-0.08268788259142047,"[5.8043132265105075e-08, 0.9999999155562016, 3.8341722580108466e-21, 2.640066607679121e-08, 3.917855331387466e-25]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,0uGlKYS7a2,Maximizing utility in multi-agent environments by anticipating the behavior of other learners,Game Theory; no regret; learning theory;,5.5,3.25,Angelos Assos;Yuval Dagan;Constantinos Costis Daskalakis,Massachusetts Institute of Technology;Massachusetts Institute of Technology,MS student;Full Professor,https://neurips.cc/virtual/2024/poster/96898,,,https://openreview.net/forum?id=0uGlKYS7a2,/media/PosterPDFs/NeurIPS%202024/96898.png?t=1731753379.9098587
9,77,-0.07488669,0.3827278,2,-0.11681432644787078,0.3248438774830968,"[0.0002329623881574467, 8.813556710204871e-18, 0.999738134740862, 1.8651593635927288e-15, 2.8902870978743117e-05]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,0uXtFk5KNJ,BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models,block coordinate descent;large language models,5.25,3.75,Qijun Luo;Hengxu Yu;Xiao Li,"The Chinese University of Hong Kong, Shenzhen;The Chinese University of Hong Kong, Shenzhen;Chinese University of Hong Kong Shen Zhen",PhD student;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96897,,,https://openreview.net/forum?id=0uXtFk5KNJ,/media/PosterPDFs/NeurIPS%202024/96897.png?t=1733743857.9232197
9,78,0.022653038,0.24370801,2,-0.11681432644787078,0.3248438774830968,"[0.36467940875555105, 1.6264947503265979e-09, 0.6285538933228102, 3.635274865563815e-08, 0.0067666599423953505]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,0zFVhMBZHJ,Mixture of Tokens: Continuous MoE through Cross-Example Aggregation,LLM;Mixture of Experts;MoE;conditional computation;fully-differentiable;language modeling,6.0,3.6666666666666665,Szymon Antoniak;Michał Krutul;Maciej Pióro;Jakub Krajewski;Jan Ludziejewski;Kamil Ciebiera;Krystian Król;Tomasz Odrzygóźdź;Marek Cygan;Sebastian Jaszczur,IDEAS NCBR Sp.;IDEAS NCBR Sp.;University of Warsaw;University of Warsaw;IDEAS NCBR Sp.;University of Warsaw;IDEAS NCBR;Nomagic;University of Warsaw,PhD student;Researcher;PhD student;PhD student;Intern;MS student;Postdoc;Founder / CTO;PhD student,https://neurips.cc/virtual/2024/poster/96896,,,https://openreview.net/forum?id=0zFVhMBZHJ,/media/PosterPDFs/NeurIPS%202024/96896.png?t=1730308223.324062
9,79,0.24368975,0.18879418,0,0.05848115929280148,0.01166383457759367,"[0.999344745105857, 0.0005687060838994695, 8.096120571741081e-05, 5.359468531043387e-06, 2.2813599498937983e-07]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,0zWzJj6lO3,Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents,cooperative AI;AI safety;LLM agents;cognitive science;language model evaluation;dynamic evaluation;alignment;agency;evolving benchmarks;multi-agent interactions,5.75,3.5,Giorgio Piatti;Zhijing Jin;Max Kleiman-Weiner;Bernhard Schölkopf;Mrinmaya Sachan;Rada Mihalcea,Common Sense Machines;University of Michigan;Swiss Federal Institute of Technology,Principal Researcher;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96895,,,https://openreview.net/forum?id=0zWzJj6lO3,
9,80,-0.16938657,-0.05973538,4,-0.20691720368450753,-0.004029014381643935,"[0.05647258156139186, 1.3692981511480614e-07, 3.479660215380223e-09, 0.0065985937277627535, 0.9369286843013699]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,0zfUiSX5si,AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases,De Novo Peptide sequencing;Proteomics;Mass Spectrum,5.333333333333333,3.0,Jun Xia;Shaorong Chen;Jingbo Zhou;Xiaojun Shan;Wenjie Du;Zhangyang Gao;Cheng Tan;Bozhen Hu;Jiangbin Zheng;Stan Z. Li,"Westlake University, China;Westlake University;Jilin University;University of Electronic Science and Technology of China;University of Science and Technology of China;Westlake University, China;Zhejiang University & Westlake University;Westlake University;Westlake University;Westlake University",PhD student;PhD student;Undergrad student;Undergrad student;Assistant Professor;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96894,,,https://openreview.net/forum?id=0zfUiSX5si,
9,81,-0.25151917,-0.28693447,3,-0.13361257096747306,-0.27899371683895335,"[0.07485781029882037, 5.052197390641925e-06, 1.6633014517253553e-21, 0.9147135621184176, 0.010423575385371487]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,105ZuvpdyW,SegVol: Universal and Interactive Volumetric Medical Image Segmentation,Volumetric Medical Image Segmentation;3D Segmentation Foundation Model;Universal and Interactive 3D Segmentation,7.666666666666667,4.333333333333333,Yuxin Du;Fan BAI;Tiejun Huang;Bo Zhao,Beijing Academy of Artificial Intelligence;The Chinese University of Hong Kong;Peking University;BAAI,Intern;PhD student;Full Professor;Principal Researcher,https://neurips.cc/virtual/2024/poster/96893,,,https://openreview.net/forum?id=105ZuvpdyW,/media/PosterPDFs/NeurIPS%202024/96893.png?t=1731410503.871179
9,82,0.04577409,-0.24324691,3,-0.13361257096747306,-0.27899371683895335,"[0.3053170892164512, 0.0698462416027747, 2.129687478438121e-21, 0.6248196808389129, 1.6988341861191455e-05]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,1067784F6e,Data Distribution Valuation,Data distribution valuation;Huber model;Maximum mean discrepancy,6.333333333333333,4.333333333333333,Xinyi Xu;Shuaiqi Wang;Chuan-Sheng Foo;Bryan Kian Hsiang Low;Giulia Fanti,"National University of Singapore;Carnegie Mellon University;Institute for Infocomm Research, A*STAR;National University of Singapore;Carnegie Mellon University",PhD student;PhD student;Principal Scientist;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96892,,,https://openreview.net/forum?id=1067784F6e,/media/PosterPDFs/NeurIPS%202024/96892.png?t=1731176029.7581189
9,83,-0.22563006,-0.049784996,4,-0.20691720368450753,-0.004029014381643935,"[0.009032303235524649, 3.0402369820802443e-09, 1.0355683074620608e-08, 0.0011026628134788161, 0.9898650205550764]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,12A1RT1L87,Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?,Dataset Condensation;Dataset Distillation,5.666666666666667,3.6666666666666665,Lingao Xiao;Yang He,"School of Computer Science and  Engineering, Nanyang Technological University;Institute of High Performance Computing, Singapore, A*STAR",Undergrad student;Researcher,https://neurips.cc/virtual/2024/poster/96891,,,https://openreview.net/forum?id=12A1RT1L87,/media/PosterPDFs/NeurIPS%202024/96891.png?t=1731138766.8349779
9,84,-0.20074943,0.040258985,4,-0.20691720368450753,-0.004029014381643935,"[0.0050891274996402, 1.2978825623515003e-10, 2.3048496739656217e-05, 2.1821802676028227e-05, 0.9948660020711558]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,135eKqDoRR,Bayesian-guided Label Mapping for Visual Reprogramming,visual reprogramming;adversarial reprogramming;output label mapping;Bayesian probability,7.25,4.0,Chengyi Cai;Zesheng Ye;Lei Feng;Jianzhong Qi;Feng Liu,University of Melbourne;Singapore University of Technology and Design;University of Melbourne;University of Melbourne,PhD student;Assistant Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96890,,,https://openreview.net/forum?id=135eKqDoRR,
9,85,-0.1496939,0.30529067,2,-0.11681432644787078,0.3248438774830968,"[8.537346626489151e-05, 2.5113654844030737e-17, 0.9986808979485949, 1.918613871481247e-13, 0.00123372858494844]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,14hLJr6kZ3,Enhancing Domain Adaptation through Prompt Gradient Alignment,transfer learning; domain adaptation; prompt-tuning,6.25,3.25,Hoang Phan;Tung Lam Tran;Quyen Tran;Trung Le,VinAi Research;VinAI Research;Monash University;New York University,Research resident;Research Resident;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96889,,,https://openreview.net/forum?id=14hLJr6kZ3,/media/PosterPDFs/NeurIPS%202024/96889.png?t=1732036918.0147438
9,86,0.2630342,0.051892787,0,0.05848115929280148,0.01166383457759367,"[0.7272346598603713, 0.2704176895652759, 4.572964759410485e-09, 0.002347531876325912, 1.1412506193320998e-07]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,15460JjocO,Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners,multi-agent;reinforcement learning;robustness;diversity;specialization,7.0,3.6666666666666665,Rujikorn Charakorn;Poramate Manoonpong;Nat Dilokthanakul,Sakana AI;Vidyasirimedhi Institute of Science and Technology;King Mongkut's Institute of Technology Ladkrabang,Intern;Full Professor;Lecturer,https://neurips.cc/virtual/2024/poster/96888,,,https://openreview.net/forum?id=15460JjocO,/media/PosterPDFs/NeurIPS%202024/96888.png?t=1731395258.7214391
9,87,0.61719507,-0.024593957,1,0.39400268802779437,-0.08268788259142047,"[1.1824297755714685e-08, 0.9999999655517291, 1.8166065791694264e-23, 2.2623973087499426e-08, 4.883579577370192e-26]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,15Jm9v7wCo,No-Regret Learning for Fair Multi-Agent Social Welfare Optimization,Online Learning;Nash Social Welfare,5.666666666666667,3.3333333333333335,Mengxiao Zhang;Ramiro Deo-Campo Vuong;Haipeng Luo,University of Southern California;University of Southern California,Undergrad student;Associate Professor,https://neurips.cc/virtual/2024/poster/96887,,,https://openreview.net/forum?id=15Jm9v7wCo,
9,88,-0.14552048,-0.15470643,3,-0.13361257096747306,-0.27899371683895335,"[0.3470032307560538, 2.6693396717135898e-05, 9.754709983606043e-14, 0.3643674261037125, 0.288602649743419]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,15PS30UOUp,Kuro Siwo: 33 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping,Synthetic Aperture Radar;SAR;Deep Learning;Remote Sensing;Floods;dataset,6.75,3.75,Nikolaos Ioannis Bountos;Maria Sdraka;Angelos Zavras;Andreas Karavias;Ilektra Karasante;Themistocles Herekakis;Angeliki Thanasou;Dimitrios Michail;Ioannis Papoutsis,National Observatory of Athens;National Observatory of Athens;Harokopio University;The Centre for Research & Technology;National Observatory of Athens ;National Observatoty of Athens;National Observatory of Athens;Harokopio University;National Technical University of Athens,PhD student;Researcher;PhD student;Researcher;Researcher;Researcher;Researcher;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97874,,,,
9,89,0.004352061,-0.07103703,0,0.05848115929280148,0.01166383457759367,"[0.8957458084955636, 0.000849109660899365, 7.902615350292144e-11, 0.08268654607883737, 0.02071853568567365]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,164QnJsYjF,Dense Associative Memory Through the Lens of Random Features,Associative Memory;Kernels;Random Features;Hopfield Network,6.0,3.0,Benjamin Hoover;Duen Horng Chau;Hendrik Strobelt;Parikshit Ram;Dmitry Krotov,International Business Machines;International Business Machines;International Business Machines;Massachusetts Institute of Technology;Georgia Institute of Technology,AI Research Engineer;Principal Researcher;Principal Researcher;Researcher;Full Professor,https://neurips.cc/virtual/2024/poster/96886,,,https://openreview.net/forum?id=164QnJsYjF,/media/PosterPDFs/NeurIPS%202024/96886.png?t=1733846086.053208
9,90,-0.31772932,0.41427824,2,-0.11681432644787078,0.3248438774830968,"[5.709009677366503e-09, 7.77037492618425e-27, 0.9999962909906975, 9.262508172568943e-21, 3.703300292882153e-06]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,168NLzTpw8,Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation,Vision-Language;Region-Level Understanding;Multimodal Large Language Model,5.75,3.75,Yaoyuan Liang;Zhuojun Cai;Jian Xu;Guanbo Huang;Yiran Wang;Xiao Liang;Jiahao Liu;Ziran Li;Jingang Wang;Shao-Lun Huang,"Tsinghua Shenzhen International Graduate School, Tsinghua University;Microsoft;University of Electronic Science and Technology of China;Tsinghua University;Tsinghua University;Meituan;Meituan;Tsinghua University",PhD student;Intern;Undergrad student;MS student;MS student;Researcher;Researcher;Associate Professor,https://neurips.cc/virtual/2024/poster/96885,,,https://openreview.net/forum?id=168NLzTpw8,
9,91,-0.118134014,0.26676714,2,-0.11681432644787078,0.3248438774830968,"[0.0012284455961316808, 9.498091309143414e-15, 0.9899598016957856, 3.157142123901704e-11, 0.008811752676501762]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,181llen2gw,A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks,Vision-Language Model;Fairness;Debias,6.333333333333333,3.6666666666666665,Hoin Jung;Taeuk Jang;Xiaoqian Wang,Purdue University;Purdue University;Purdue University,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96884,,,https://openreview.net/forum?id=181llen2gw,/media/PosterPDFs/NeurIPS%202024/96884.png?t=1731379505.2628894
9,92,-0.19037005,0.30377576,2,-0.11681432644787078,0.3248438774830968,"[1.8122218346735265e-05, 1.4932548136888925e-18, 0.9987111547849739, 5.167592659494909e-14, 0.001270722996627684]","[0.010044125364410458, 0.0038543569641372394]",0.17531666039159804,18FGRNd0wZ,Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation,tokenization of crystals;language models;materials generation,6.0,3.5,Keqiang Yan;Xiner Li;Hongyi Ling;Kenna Ashen;Carl Edwards;Raymundo Arroyave;Marinka Zitnik;Heng Ji;Xiaofeng Qian;Xiaoning Qian;Shuiwang Ji,"Texas A&M University;Texas A&M University - College Station;Texas A&M University - College Station;Texas A&M University - College Station;Genentech;Texas A&M University Main Campus;Harvard University;University of Illinois, Urbana-Champaign;Texas A&M University;Texas A&M;Texas A&M University",PhD student;PhD student;PhD student;PhD student;Intern;Assistant Professor;Full Professor;Associate Professor;Full Professor;Professor,https://neurips.cc/virtual/2024/poster/96883,,,https://openreview.net/forum?id=18FGRNd0wZ,/media/PosterPDFs/NeurIPS%202024/96883.png?t=1733428872.6393995
9,93,-0.18803668,0.09546091,4,-0.20691720368450753,-0.004029014381643935,"[0.005095651132150229, 1.9103139789041706e-11, 0.0016572984615480012, 1.9092326682837245e-06, 0.9932451411545303]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,18RdkSv9h9,FINALLY: fast and universal speech enhancement with studio-like quality,speech enhancement; generative models,6.5,4.75,Nicholas Babaev;Kirill Tamogashev;Azat Saginbaev;Ivan Shchekotov;Hanbin Bae;Hosang Sung;WonJun Lee;Hoon-Young Cho;Pavel Andreev,"Samsung;Skolkovo Institute of Science and Technology;Moscow Institute of Physics and Technology;Samsung;Samsung;Samsung;Higher School of Economics, Higher School of Economics",Researcher;MS student;MS student;Principal Researcher;Researcher;Vice President;MS student,https://neurips.cc/virtual/2024/poster/96882,,,https://openreview.net/forum?id=18RdkSv9h9,/media/PosterPDFs/NeurIPS%202024/96882.png?t=1731683595.700073
9,94,0.32727078,-0.11709024,1,0.39400268802779437,-0.08268788259142047,"[0.001082529200955339, 0.9981093157190735, 1.0655802239344202e-19, 0.0008081550790345317, 9.368094309690359e-13]","[0.017884027192240696, 0.012298194646037874]",0.19497387693172938,1ATLLgvURu,Learning-Augmented Priority Queues,learning-augmented algorithms;algorithms with predictions;priority queue;shortest paths;Dijkstra,5.75,4.25,Ziyad Benomar;Christian Coester,University of Oxford,Associate Professor,https://neurips.cc/virtual/2024/poster/96881,,,https://openreview.net/forum?id=1ATLLgvURu,
9,95,0.3095995,0.5030761,0,0.05848115929280148,0.01166383457759367,"[0.9984316916838644, 1.8995899059997132e-10, 0.0015683081256632132, 3.3549024754741268e-15, 5.098714570365177e-13]","[0.016081105983317974, 0.03132867959378998]",0.23647204882880574,1BZKqZphsW,Risk-Averse Fine-tuning of Large Language Models,Risk Averse Reinforcement Learning;Large Language Model Finetuning,5.8,3.2,Sapana Chaudhary;Ujwal Dinesha;Dileep Kalathil;Srinivas Shakkottai,Texas A&M University;Texas A&M University - College Station;Texas A&M University;Texas A&M,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96880,,,https://openreview.net/forum?id=1BZKqZphsW,/media/PosterPDFs/NeurIPS%202024/96880.png?t=1733328781.5713553
9,96,-0.26364937,-0.38828564,3,-0.13361257096747306,-0.27899371683895335,"[0.06172164473946201, 1.1966257895336897e-05, 4.7409330131464084e-29, 0.9381760209566994, 9.036804594340826e-05]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,1CssOqRYyz,Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds,compression;point cloud;diffusion,4.0,4.0,Kai Liu;Kang You;Pan Gao,"Nanjing University of Aeronautics and Astronautics;Nanjing university;Nanjing University of Aeronautics and Astronautics, Tsinghua University",MS student;PhD student;Associate Professor,,,,,
9,97,-0.25224024,-0.31188005,3,-0.13361257096747306,-0.27899371683895335,"[0.06677422551387255, 6.606326778813353e-06, 2.497412621536956e-23, 0.9300461042273425, 0.0031730639320062667]","[0.014793374286136208, 0.008303041163908956]",0.1527555429650604,1Du3mMP5YN,Learning to Shape In-distribution Feature Space for Out-of-distribution Detection,Out-of-distribution Detection,5.75,4.0,Yonggang Zhang;Jie Lu;Bo Peng;Zhen Fang;Yiu-ming Cheung,Hong Kong Baptist University;University of Technology Sydney;University of Technology Sydney,Postdoc;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96879,,,https://openreview.net/forum?id=1Du3mMP5YN,/media/PosterPDFs/NeurIPS%202024/96879.png?t=1731745181.7993424
9,98,-0.30068702,-0.14781809,4,-0.20691720368450753,-0.004029014381643935,"[0.014269443153874935, 1.256741186007341e-08, 1.1499697387746755e-12, 0.04065733814765877, 0.9450732061299045]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,1ELFGSNBGC,Multiview Scene Graph,scene representation; spatial understanding; place recognition; object correspondence; scene graph,5.25,3.25,Juexiao Zhang;Gao Zhu;Sihang Li;Xinhao Liu;Haorui Song;Xinran Tang;Chen Feng,New York University;New York University;New York University;New York University;New York University;New York University;New York University,PhD student;MS student;PhD student;PhD student;MS student;MS student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96878,,,https://openreview.net/forum?id=1ELFGSNBGC,/media/PosterPDFs/NeurIPS%202024/96878.png?t=1731728482.5838113
9,99,-0.09486352,0.005280091,4,-0.20691720368450753,-0.004029014381643935,"[0.22302408507267107, 5.975962743492423e-07, 1.121078487227154e-06, 0.0022677572734604097, 0.774706438979107]","[0.006013933954037172, 0.00677586863352445]",0.24048187088280656,1F32iCJFfa,Schrodinger Bridge Flow for Unpaired Data Translation,unpaired data translation;diffusion models;Schrodinger bridge;bridge matching;stochastic interpolant;flow matching,6.5,4.0,Valentin De Bortoli;Iryna Korshunova;Andriy Mnih;Arnaud Doucet,University of Oxford;Google DeepMind;Google DeepMind;University of Oxford,Postdoc;Researcher;Research Scientist;Full Professor,https://neurips.cc/virtual/2024/poster/96877,,,https://openreview.net/forum?id=1F32iCJFfa,/media/PosterPDFs/NeurIPS%202024/96877.png?t=1731688420.732189
10,0,0.08799766,-0.06060414,0,0.06371267907187256,0.011393023405034543,"[0.9185523381736995, 0.001921578259717476, 1.0449222155051056e-11, 0.07921555725189916, 0.00031052630423460657]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,00Sx577BT3,The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning,numerical simulations;fluid-dynamics;partial differential equations;operator learning,6.666666666666667,3.6666666666666665,Ruben Ohana;Michael McCabe;Lucas Thibaut Meyer;Rudy Morel;Fruzsina Julia Agocs;Miguel Beneitez;Marsha Berger;Blakesley Burkhart;Stuart B. Dalziel;Drummond Buschman Fielding;Daniel Fortunato;Jared A. Goldberg;Keiya Hirashima;Yan-Fei Jiang;Rich Kerswell;Suryanarayana Maddu;Jonah M. Miller;Payel Mukhopadhyay;Stefan S. Nixon;Jeff Shen;Romain Watteaux;Bruno Régaldo-Saint Blancard;François Rozet;Liam Holden Parker;Miles Cranmer;Shirley Ho,"Flatiron Institute;University of Colorado, Boulder;INRIA;Flatiron Institute;Flatiron Institute;University of Cambridge;Flatiron Institute;Rutgers University;University of Cambridge;Simons Foundation;Flatiron Institute;Flatiron Institute;Simons Foundation;University of Cambridge;Flatiron Institute/Simons Foundation;Los Alamos National Laboratory;University of California, Berkeley;University of Cambridge;Princeton University;CEA;Flatiron Institute;Flatiron Institute;Flatiron Institute;University of Cambridge;Carnegie Mellon University;The University of Tokyo",Postdoc;PhD student;PhD student;Postdoc;Postdoc;Postdoc;Full Professor;Assistant Professor;Director of the GK Batchelor Laboratory;Postdoc;Researcher;Postdoc;Researcher;Full Professor;Postdoc;Researcher;Postdoc;PhD student;PhD student;Researcher;Postdoc;Intern;Researcher;Assistant Professor;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/97882,,,,
10,1,-0.08406016,0.2851326,2,-0.09463330063911646,0.3327342704201369,"[0.0027978109744911596, 8.455544974964053e-18, 0.9946553574554455, 1.037925945458185e-10, 0.002546831466270655]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,00uVk06eVK,On the Noise Robustness of In-Context Learning for Text Generation,In-Context Learning;Large Language Models;Noise Robustness,6.333333333333333,3.0,Hongfu Gao;Feipeng Zhang;Wenyu Jiang;Jun Shu;Feng Zheng;Hongxin Wei,Xi'an Jiaotong University;Xi'an Jiaotong University;Nanjing University;Xi'an Jiaotong University;Southern University of Science and Technology;Southern University of Science and Technology,MS student;Full Professor;PhD student;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96962,,,https://openreview.net/forum?id=00uVk06eVK,/media/PosterPDFs/NeurIPS%202024/96962.png?t=1731587881.4159098
10,2,-0.16364236,-0.11411294,4,-0.20931696028541216,-0.0035235230900599545,"[0.18743064225161032, 3.759188994318282e-08, 1.3966807045358723e-10, 0.12348207309061122, 0.6890872469262205]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,01I55gys19,Few-Class Arena: A Benchmark for Efficient Vision Model Selection and Dataset Difficulty,few-class;efficiency;neural network;convolutional neural network;transformer;dataset difficulty measurement;scaling law,5.0,3.3333333333333335,Bryan Bo Cao;Lawrence O'Gorman;Michael Coss;Shubham Jain,Nokia networks GmbH;State University of New York at Stony Brook,Intern;Assistant Professor,,,,,
10,3,0.07371062,-0.27021888,3,-0.12517292191148427,-0.27255963411007533,"[0.12969337108104045, 0.11035775973034086, 1.8225486728762164e-23, 0.7599483445825462, 5.246060723735708e-07]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,01XV5Za56k,Testing Calibration in Nearly-Linear Time,Calibration;Property testing;Linear programming,6.25,3.25,Lunjia Hu;Arun Jambulapati;Kevin Tian;Chutong Yang,Stanford University;Stanford University;Stanford University;University of Texas at Austin,PhD student;PhD student;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96961,,,https://openreview.net/forum?id=01XV5Za56k,
10,4,-0.1284643,0.3103237,2,-0.09463330063911646,0.3327342704201369,"[0.0002675658761969058, 8.686358228288612e-21, 0.9989501089776125, 2.0265944649326375e-12, 0.0007823251441640336]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,01lhHg8H9p,GLBench: A Comprehensive Benchmark for Graph with Large Language Models,Graph learning;Large Language Model;Zero-Shot,6.75,4.0,Yuhan Li;Peisong Wang;Xiao Zhu;Aochuan Chen;Haiyun Jiang;Deng Cai;Victor Wai Kin Chan;Jia Li,"Hong Kong University of Science and Technology;Tsinghua University;Beijing University of Posts and Telecommunications;Hong Kong University of Science and Technology;Tencent AI Lab;Tencent AI Lab;Shenzhen International Graduate School, Tsinghua University;Hong Kong University of Science and Technology",PhD student;MS student;Undergrad student;PhD student;Researcher;Research Scientist;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97881,,,,/media/PosterPDFs/NeurIPS%202024/97881.png?t=1731478194.2539835
10,5,-0.23808402,0.26056772,2,-0.09463330063911646,0.3327342704201369,"[5.153954483916007e-05, 5.1583050311003706e-23, 0.9933715748774855, 5.195469775078045e-12, 0.0065768855724799005]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,01qa1ZJs65,Bridge the Modality and Capability Gaps in Vision-Language Model Selection,Vision-Language Model;Model Selection;Zero-Shot Image Classification,5.25,4.0,Chao Yi;Yuhang He;De-Chuan Zhan;Han-Jia Ye,Nanjing University;Nanjing University;Nanjing University;Nanjing University,MS student;Undergrad student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96960,,,https://openreview.net/forum?id=01qa1ZJs65,/media/PosterPDFs/NeurIPS%202024/96960.png?t=1731123927.9174762
10,6,-0.10493148,-0.30384988,3,-0.12517292191148427,-0.27255963411007533,"[0.042407722321485986, 0.0001304102504035187, 1.3507835917647849e-22, 0.9573534670801718, 0.00010840034793863528]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,01s5ODIHKd,FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space,deep watermarking;latent frequency optimization,5.5,3.75,YiYang Guo;Ruizhe Li;Mude Hui;Hanzhong Allan Guo;Chen Zhang;Chuangjian Cai;Le Wan;Shangfei Wang,"University of Science and Technology of China;University of California, Santa Cruz;Renmin University of China;Tsinghua University;University of Science and Technology of China;University of Science and Technology of China",MS student;PhD student;MS student;PhD student;Full Professor;PhD student,https://neurips.cc/virtual/2024/poster/96959,,,https://openreview.net/forum?id=01s5ODIHKd,/media/PosterPDFs/NeurIPS%202024/96959.png?t=1730176108.8718698
10,7,-0.295713,-0.42771262,3,-0.12517292191148427,-0.27255963411007533,"[0.0029009398280190678, 3.5199732914549805e-07, 1.3373002221258966e-27, 0.9970918097805075, 6.898394144359987e-06]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,02CIZ8qeDc,PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection,3D anomaly detection;Zero-shot 3D anomaly detection,6.0,3.6666666666666665,Qihang Zhou;Jiangtao Yan;Shibo He;Wenchao Meng;Jiming Chen,Zhejiang University;Zhejiang University;Zhejiang University;Zhejiang University,PhD student;MS student;Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96958,,,https://openreview.net/forum?id=02CIZ8qeDc,/media/PosterPDFs/NeurIPS%202024/96958.png?t=1731476864.9817398
10,8,-0.3188932,-0.023905918,4,-0.20931696028541216,-0.0035235230900599545,"[0.0017189766974602776, 1.4283260859940418e-15, 7.377879468842974e-06, 0.00010916910957041939, 0.998164476313499]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,02HWT9c4Lp,Voxel Proposal Network via Multi-Frame Knowledge Distillation for Semantic Scene Completion,Semantic Scene completion，Voxel Proposal，Knowledge Distillation,5.5,4.0,Lubo Wang;Di Lin;Kairui Yang;Ruonan Liu;Qing Guo;Wuyuan Xie;Miaohui Wang;Lingyu Liang;Yi Wang;Ping Li,"Tianjin University;Tianjin University;Tianjin University;Tianjin University; Agency for Science, Technology and Research (A*STAR));Department of Software Engineering, Shenzhen University;Shenzhen University;South China University of Technology;Shenzhen University;The Hong Kong Polytechnic University",MS student;Associate Professor;PhD student;Associate Professor;Researcher;Associate Professor;Associate Professor;Associate Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96957,,,https://openreview.net/forum?id=02HWT9c4Lp,/media/PosterPDFs/NeurIPS%202024/96957.png?t=1731159292.6143699
10,9,0.52375084,0.03593809,1,0.4075643889177964,-0.08207163922598883,"[9.714592626893687e-05, 0.9999015193682009, 6.792624532417298e-17, 1.3347055301418194e-06, 4.526616558558496e-21]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,02r24A8doi,Achieving Constant Regret in Linear Markov Decision Processes,Reinforcement learning;Constant regret;Misspecified linear MDP,5.25,2.75,Weitong Zhang;Zhiyuan Fan;Jiafan He;Quanquan Gu,"Massachusetts Institute of Technology;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles",PhD student;PhD student;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96956,,,https://openreview.net/forum?id=02r24A8doi,
10,10,-0.24769914,0.06194072,4,-0.20931696028541216,-0.0035235230900599545,"[0.0032213708555595758, 8.619125342555872e-16, 0.0007634574387930448, 5.7743008009111214e-06, 0.9960093974048455]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,04EC4ZnZJj,MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers,transformer architecture;large language model;computational complexity reduction,6.0,3.5,Ning Ding;Yehui Tang;Haochen Qin;Zhenli Zhou;Chao Xu;Lin Li;Kai Han;Liao Heng;Yunhe Wang,"Peking University;Huawei Technologies Ltd.;Huawei Technologies Ltd.;Peking University;Peking University;Huawei Noah's Ark Lab;, Tsinghua University;Huawei Noah's Ark Lab",PhD student;Researcher;Researcher;MS student;Full Professor;Principal Researcher;Principal Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96955,,,https://openreview.net/forum?id=04EC4ZnZJj,
10,11,0.45866024,0.07679337,1,0.4075643889177964,-0.08207163922598883,"[0.004636918925361411, 0.9953491152999056, 7.212672667372501e-13, 1.396577401193389e-05, 7.624874366094137e-17]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,06JRFVK88O,Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games,Multi-agent Reinforcement Learning;Imitation Learning,6.666666666666667,3.0,The Viet Bui;Tien Anh Mai;Thanh Hong Nguyen,Singapore Management University;University of Oregon;Singapore Management University,Assistant Professor;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96954,,,https://openreview.net/forum?id=06JRFVK88O,/media/PosterPDFs/NeurIPS%202024/96954.png?t=1731744891.8886228
10,12,-0.21952832,-0.2596673,3,-0.12517292191148427,-0.27255963411007533,"[0.039601414583404486, 2.8455313290017635e-07, 1.1368979170774886e-17, 0.9459535819586813, 0.014444718904781323]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,06Vt6f2js7,SyncTweedies: A General Generative Framework Based on Synchronized Diffusions,Diffusion Models;Synchronization;Texturing;3D Gaussian Splatting;Mesh;Panorama,6.666666666666667,3.6666666666666665,Jaihoon Kim;Juil Koo;Kyeongmin Yeo;Minhyuk Sung,KAIST;Adobe Systems;Korea Advanced Institute of Science & Technology;Korea Advanced Institute of Science & Technology,MS student;Intern;Undergrad student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96953,,,https://openreview.net/forum?id=06Vt6f2js7,
10,13,0.5387558,-0.021885695,1,0.4075643889177964,-0.08207163922598883,"[1.4092531151475186e-05, 0.9999850051221746, 1.589951264179696e-20, 9.023466740252486e-07, 9.597889113778822e-23]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,07N0qoaZ2L,Improved Analysis for Bandit Learning in Matching Markets,Bandits;Matching markets;Stable matching;Stable regret;Exploration and exploitation;$\alpha$-condition,5.5,3.0,Fang Kong;Zilong Wang;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;John Hopcroft Center, Shanghai Jiao Tong University",PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96952,,,https://openreview.net/forum?id=07N0qoaZ2L,/media/PosterPDFs/NeurIPS%202024/96952.png?t=1731746661.9360106
10,14,-0.31746334,-0.03755091,4,-0.20931696028541216,-0.0035235230900599545,"[0.0021019833616200425, 4.091910093602612e-15, 2.5072040070113995e-06, 0.00021782290057109302, 0.9976776865337978]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,08A6X7FSTs,Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text,Text-to-3D Scene Generation;Latent Diffusion Models,5.5,4.5,Xinyang Li;Zhangyu Lai;Linning Xu;Yansong Qu;Liujuan Cao;Shengchuan Zhang;Bo Dai;Rongrong Ji,Xiamen University;Xiamen University;Xiamen University;Xiamen University;Xiamen University;Shanghai AI Laboratory;Xiamen University;The Chinese University of Hong Kong,PhD student;MS student;PhD student;Full Professor;Assistant Professor;Scientist;Full Professor;Ph.D. student,https://neurips.cc/virtual/2024/poster/96951,,,https://openreview.net/forum?id=08A6X7FSTs,/media/PosterPDFs/NeurIPS%202024/96951.png?t=1732593534.8700738
10,15,0.21572201,0.15297481,0,0.06371267907187256,0.011393023405034543,"[0.9997754625231997, 0.0001224606425232549, 3.461031700940087e-05, 6.654918730453022e-05, 9.173299628043345e-07]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,08GbdALmEs,Learning Versatile Skills with Curriculum Masking,reinforcement learning;unsupervised pretraining;masked prediction;curriculum learning,5.25,3.25,Yao Tang;Zhihui Xie;Zichuan Lin;Deheng Ye;Shuai Li,"Shanghai Jiaotong University;Shanghai Jiaotong University;Tencent AI Lab;Tencent;John Hopcroft Center, Shanghai Jiao Tong University",Undergrad student;MS student;Researcher;Principal Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96950,,,https://openreview.net/forum?id=08GbdALmEs,/media/PosterPDFs/NeurIPS%202024/96950.png?t=1733319308.3295946
10,16,-0.17784788,-0.16018736,3,-0.12517292191148427,-0.27255963411007533,"[0.1877194094887068, 1.4774856271001063e-07, 1.5585919740039068e-12, 0.43564901731923783, 0.3766314254419341]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,08nbMTxazb,Chicks4FreeID: A Benchmark Dataset for Chicken Re-Identification,animal re-identification;chicken re-identification;chicken dataset;re-identification dataset;benchmark dataset;closed-set re-identification;computer vision;chicken instance segmentation;poultry;livestock,4.75,4.0,Daria Kern;Tobias Schiele;Ulrich Klauck;Winfred Ingabire,Glasgow Caledonian University;Hochschule Aalen;Glasgow Caledonian University,PhD student;Full Professor;Lecturer,,,,,
10,17,0.12485067,-0.17534988,3,-0.12517292191148427,-0.27255963411007533,"[0.3853170918144676, 0.17079614434086507, 2.0904408332413398e-18, 0.4438850298751164, 1.7339695510416029e-06]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,08oUnmtj8Q,FSEO: A Few-Shot Evolutionary Optimization Framework for Expensive Multi-Objective Optimization and Constrained Optimization,Expensive optimization;few-shot optimization;multi-objective optimization;constrained optimization;surrogate-assisted evolutionary optimization,4.5,3.5,Xunzhao Yu,,,,,,,
10,18,-0.045080878,-0.32160506,3,-0.12517292191148427,-0.27255963411007533,"[0.04933796309947859, 0.0022716306152976724, 7.877676901631493e-25, 0.9483835133705683, 6.892914655549388e-06]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,09RKw0vXjR,Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations,feature selection;sparse coding;dictionary learning;compressed sensing;iterative hard thresholding;pruning method,5.75,3.0,Yasutoshi Ida;Sekitoshi Kanai;Atsutoshi Kumagai;Tomoharu Iwata;Yasuhiro Fujiwara,NTT;NTT;NTT;NTT;NTT,Researcher;Researcher;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96949,,,https://openreview.net/forum?id=09RKw0vXjR,/media/PosterPDFs/NeurIPS%202024/96949.png?t=1733375377.8112724
10,19,-0.29219365,-0.1354431,4,-0.20931696028541216,-0.0035235230900599545,"[0.01777571165086106, 2.1643090191691794e-11, 4.1659454023215327e-10, 0.03748964242324648, 0.9447346454876548]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,09nyBqSdUz,RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance,Consistent image generation;Diverse image generation;Improve temporal-consistency;Feature injection from multiple images,5.5,4.0,Jiaojiao Fan;Haotian Xue;Qinsheng Zhang;Yongxin Chen,Georgia Institute of Technology;Georgia Institute of Technology;Georgia Institute of Technology;NVIDIA,PhD student;PhD student;Associate Professor;Research Intern,https://neurips.cc/virtual/2024/poster/96948,,,https://openreview.net/forum?id=09nyBqSdUz,/media/PosterPDFs/NeurIPS%202024/96948.png?t=1731392354.7708242
10,20,0.22983314,0.005944166,0,0.06371267907187256,0.011393023405034543,"[0.899326729834251, 0.0886521268288115, 7.995371298052196e-11, 0.012020946671420193, 1.9658556353846553e-07]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0AumdfLzpK,A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations,Visual Reinforcement Learning;Generalization,6.0,4.0,Wonil Song;Hyesong Choi;Kwanghoon Sohn;Dongbo Min,Yonsei Univ.;Ewha Womans University;Yonsei University;Ewha Womans University,PhD student;PhD student;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96947,,,https://openreview.net/forum?id=0AumdfLzpK,/media/PosterPDFs/NeurIPS%202024/96947.png?t=1732451612.1247888
10,21,-0.2313607,0.15489271,4,-0.20931696028541216,-0.0035235230900599545,"[0.0032778426217407726, 6.854230498187877e-18, 0.223933104984712, 8.595830785220755e-08, 0.7727889664352394]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0AwMciNShl,"Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability, Reproducibility, and Practicality",Human evaluation;text-to-video models,5.25,4.0,Tianle Zhang;Langtian Ma;Yuchen Yan;Yuchen Zhang;Yue Yang;Ziyao Guo;Wenqi Shao;Kai Wang;Yang You;Yu Qiao;Ping Luo;Kaipeng Zhang,University of Electronic Science and Technology of China;Southern University of Science and Technology;The University of Nottingham Ningbo China;University of Electronic Science and Technology of China;Xidian University;Shanghai AI Laboratory;National University of Singapore;National University of Singapore;Shanghai AI Laboratory;The University of Hong Kong;Shanghai Jiaotong University,Undergrad student;Undergrad student;Undergrad student;Undergrad student;MS student;Researcher;PhD student;Professor;Researcher;Associate Professor;PhD student,https://neurips.cc/virtual/2024/poster/96946,,,https://openreview.net/forum?id=0AwMciNShl,/media/PosterPDFs/NeurIPS%202024/96946.png?t=1729079669.652648
10,22,0.44196302,-0.22339565,1,0.4075643889177964,-0.08207163922598883,"[1.3217250427862592e-05, 0.9999664863263852, 2.045713987397495e-30, 2.029642318683203e-05, 5.694860443334891e-21]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0C3bLHwjsY,Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions,Online Matching;Competitive Analysis;Fairness Maximization,6.25,3.0,Will Ma;Pan Xu,Columbia University;New Jersey Institute of Technology,Assistant Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96945,,,https://openreview.net/forum?id=0C3bLHwjsY,/media/PosterPDFs/NeurIPS%202024/96945.png?t=1731641014.5806563
10,23,0.31953293,-0.23248373,1,0.4075643889177964,-0.08207163922598883,"[0.0005694200836219185, 0.9983595465331606, 1.3937880210955713e-27, 0.0010710333832151993, 2.3252686580983627e-15]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0DE1dLMW2b,Quantum algorithm for large-scale market equilibrium computation,market equilibrium computation;quantum algorithm,6.0,2.75,Po-Wei Huang;Patrick Rebentrost,Centre for Quantum Technologies;National University of Singapore,Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96944,,,https://openreview.net/forum?id=0DE1dLMW2b,/media/PosterPDFs/NeurIPS%202024/96944.png?t=1731426989.5298698
10,24,0.0025802255,-0.08199731,0,0.06371267907187256,0.011393023405034543,"[0.8424653609962997, 8.891460340024647e-05, 2.3211070816587935e-11, 0.14544279470810595, 0.012002929668983147]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0EfUYVMrLv,Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment,non-stationary environments;continuous distribution shift;test-time adaptation;unlabeled data,6.666666666666667,4.0,Zhen-Yu Zhang;Zhiyu Xie;Huaxiu Yao;Masashi Sugiyama,"RIKEN;Stanford University;Department of Computer Science, University of North Carolina at Chapel Hill;The University of Tokyo",Postdoc;MS student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96943,,,https://openreview.net/forum?id=0EfUYVMrLv,/media/PosterPDFs/NeurIPS%202024/96943.png?t=1731687693.6296034
10,25,0.023439856,-0.079839304,0,0.06371267907187256,0.011393023405034543,"[0.859691933481304, 0.00021248513520183003, 1.353850642224452e-11, 0.13513698179707062, 0.004958599572885195]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0G0VpMjKyV,Sketching for Distributed Deep Learning: A Sharper Analysis,sketching;distributed learning;federated learning;optimization,5.666666666666667,4.0,Mayank Shrivastava;Berivan Isik;Qiaobo Li;Sanmi Koyejo;Arindam Banerjee,"University of Illinois, Urbana Champaign;Stanford University;Department of Computer Science, University of Illinois at Urbana-Champaign;University of Illinois, Urbana Champaign;Google",MS student;PhD student;PhD student;Professor;Research Scientist,https://neurips.cc/virtual/2024/poster/96942,,,https://openreview.net/forum?id=0G0VpMjKyV,/media/PosterPDFs/NeurIPS%202024/96942.png?t=1733481266.9121125
10,26,-0.06371302,0.3954228,2,-0.09463330063911646,0.3327342704201369,"[0.0001337661687613764, 6.630229748374825e-22, 0.9998589698126701, 7.389539518032139e-15, 7.2640185612232314e-06]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,0G5OK5vmmg,WenMind: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Classical Literature and Language Arts,Benchmark;Large Language Models;Classical Chinese Literature and Language Arts,6.25,2.75,Jiahuan Cao;Yang Liu;Yongxin Shi;Kai Ding;Lianwen Jin,South China University of Technology;South China University of Technology;South China University of Technology;INTSIG Information;South China University of Technology,MS student;MS student;PhD student;Researcher;Professor,https://neurips.cc/virtual/2024/poster/97880,,,,/media/PosterPDFs/NeurIPS%202024/97880.png?t=1730896668.2191207
10,27,-0.2963673,0.015343715,4,-0.20931696028541216,-0.0035235230900599545,"[0.0016640694212751118, 4.789837698715879e-16, 7.560810146701618e-05, 2.2083917078381522e-05, 0.9982382385601788]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0G8AXwtmy2,T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition,harmful dataset;harmful content detection;Vision Language Model,6.5,3.75,Chen Yeh;You-Ming Chang;Wei-Chen Chiu;Ning Yu,National Yang Ming Chiao Tung University;National Yang Ming Chiao Tung University;National Chiao Tung University,MS student;MS student;Associate Professor,https://neurips.cc/virtual/2024/poster/97879,,,,/media/PosterPDFs/NeurIPS%202024/97879.png?t=1730218737.4487233
10,28,0.08612508,0.3898904,2,-0.09463330063911646,0.3327342704201369,"[0.006925155970866421, 8.528462232239681e-16, 0.993074336550179, 1.2982884335422643e-12, 5.074776554507674e-07]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,0Gl5WxY6es,Grounding Multimodal Large Language Models in Actions,Embodied AI;Multimodal Large Language Models;Reinforcement Learning;Imitation Learning,6.0,3.6666666666666665,Andrew Szot;Bogdan Mazoure;Harsh Agrawal;R Devon Hjelm;Zsolt Kira;Alexander T Toshev,Georgia Institute of Technology;Apple;Apple;Apple;Georgia Institute of Technology;Apple,PhD student;Research Scientist;Researcher;Researcher;Assistant Professor;research scientist,https://neurips.cc/virtual/2024/poster/96941,,,https://openreview.net/forum?id=0Gl5WxY6es,
10,29,-0.20296153,0.2345368,2,-0.09463330063911646,0.3327342704201369,"[0.0005407223747136365, 3.100887813640843e-20, 0.9614119892469148, 2.429004413731497e-10, 0.03804728813547122]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,0Gmi8TkUC7,GenAI Arena: An Open Evaluation Platform for Generative Models,Evaluation;Benchmark;Platform;Generative Model,6.0,3.5,Dongfu Jiang;Max Ku;Tianle Li;Yuansheng Ni;Shizhuo Sun;Rongqi Fan;Wenhu Chen,Allen Institute for Artificial Intelligence;University of Waterloo;University of Waterloo;University of Toronto;NVIDIA;University of Waterloo,Intern;MS student;MS student;Undergrad student;Intern;Assistant Professor,https://neurips.cc/virtual/2024/poster/97878,,,,/media/PosterPDFs/NeurIPS%202024/97878.png?t=1730329031.3167162
10,30,-0.3021013,-0.23802479,3,-0.12517292191148427,-0.27255963411007533,"[0.030669216470005, 2.6577047679662176e-09, 7.760681179667248e-15, 0.8388880735345344, 0.13044270733774788]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,0HRRNEAQFp,A General Protocol to Probe Large Vision Models for 3D Physical Understanding,3D physical scene understanding; Representation probing protocol; Benchmark and evaluation,6.333333333333333,4.0,Guanqi Zhan;Chuanxia Zheng;Weidi Xie;Andrew Zisserman,University of Oxford;University of Oxford;Shanghai Jiaotong University,PhD student;Postdoc;Associate Professor,https://neurips.cc/virtual/2024/poster/96940,,,https://openreview.net/forum?id=0HRRNEAQFp,/media/PosterPDFs/NeurIPS%202024/96940.png?t=1731705235.0575316
10,31,0.40233114,0.06031101,1,0.4075643889177964,-0.08207163922598883,"[0.031102806713665224, 0.9687730310252185, 4.107295979882686e-12, 0.00012416225696279366, 4.6194040366174914e-14]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0JSKjdePGq,When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL,reinforcement learning;continuous-time,6.75,3.25,Lenart Treven;Bhavya Sukhija;Yarden As;Florian Dorfler;Andreas Krause,"Swiss Federal Institute of Technology;ETHZ - ETH Zurich;Department of Computer Science, ETHZ - ETH Zurich;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96939,,,https://openreview.net/forum?id=0JSKjdePGq,/media/PosterPDFs/NeurIPS%202024/96939.png?t=1730197260.75527
10,32,-0.31179968,-0.050893012,4,-0.20931696028541216,-0.0035235230900599545,"[0.0027910896725076378, 1.5406328290967595e-14, 7.621987925359991e-07, 0.0004526463580358084, 0.9967555017706486]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0KseSacluJ,CoFie: Learning Compact Neural Surface Representations with Coordinate Fields,Neural Surface Representation;Shape Auto-Decoding;Coordinate Field.,5.0,4.0,Hanwen Jiang;Haitao Yang;Georgios Pavlakos;Qixing Huang,University of Texas at Austin;The University of Texas at Austin;University of Texas at Austin;University of Texas at Austin,PhD student;PhD student;Assistant Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96938,,,https://openreview.net/forum?id=0KseSacluJ,
10,33,0.11298243,0.035079706,0,0.06371267907187256,0.011393023405034543,"[0.9951221797895398, 0.0001402431761216719, 5.285582659400868e-08, 0.004465372008680885, 0.0002721521698310166]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0KvYLaTBTE,Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference,Generative models;Reinforcement learning;Decision transformer,6.333333333333333,3.0,Deqian Kong;Dehong Xu;Minglu Zhao;Bo Pang;Jianwen Xie;Andrew Lizarraga;Yuhao Huang;Sirui Xie;Ying Nian Wu,"University of California, Los Angeles;Amazon;University of California, Los Angeles;University of California, Los Angeles;Xi'an Jiaotong University;University of California, Los Angeles;University of California, Los Angeles;UCLA",PhD student;Intern;PhD student;PhD student;PhD student;PhD student;PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96937,,,https://openreview.net/forum?id=0KvYLaTBTE,
10,34,-0.23456638,0.06657637,4,-0.20931696028541216,-0.0035235230900599545,"[0.004260506006691921, 1.7985653756750377e-15, 0.0008460808719224507, 6.1589944159175726e-06, 0.994887254126968]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0LXotew9Du,KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization,Quantization;KV Cache;LLM Inference;Compression;Long Context Length,6.25,3.25,Coleman Richard Charles Hooper;Sehoon Kim;Hiva Mohammadzadeh;Michael W. Mahoney;Sophia Shao;Kurt Keutzer;Amir Gholami,"University of California, Berkeley;University of California, Berkeley;University of California, Berkeley;University of California, Berkeley",PhD student;PhD student;Assistant Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96936,,,https://openreview.net/forum?id=0LXotew9Du,
10,35,0.11017645,-0.16371755,0,0.06371267907187256,0.011393023405034543,"[0.46954960811993585, 0.08299769964232176, 1.875950022659734e-17, 0.44744643490874, 6.257329002477241e-06]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0Lb8vZT1DB,Reliable Learning of Halfspaces under Gaussian Marginals,reliable learning;agnostic learning;halfspace;proper leaning;statistical query,7.25,2.25,Ilias Diakonikolas;Lisheng Ren;Nikos Zarifis,"University of Wisconsin - Madison;University of Wisconsin - Madison;University of Wisconsin, Madison",Full Professor;PhD student;PhD student,https://neurips.cc/virtual/2024/poster/96935,,,https://openreview.net/forum?id=0Lb8vZT1DB,
10,36,0.1429859,0.059452157,0,0.06371267907187256,0.011393023405034543,"[0.9977390097728488, 0.00020984736934075406, 1.735612765331006e-07, 0.001989872962281589, 6.109633425232669e-05]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0LfgE6kvKZ,Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning,Federated Learning; Model Merging,5.0,3.6666666666666665,Minghui Chen;Meirui Jiang;Xin Zhang;Qi Dou;Zehua Wang;Xiaoxiao Li,"University of British Columbia;Meta Facebook;The Chinese University of Hong Kong;University of British Columbia;University of British Columbia;Department of Computer Science and Engineering, The Chinese University of Hong Kong",PhD student;Research Scientist;Assistant Professor;Researcher;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96934,,,https://openreview.net/forum?id=0LfgE6kvKZ,/media/PosterPDFs/NeurIPS%202024/96934.png?t=1731518093.5294044
10,37,-0.040502112,0.02318828,0,0.06371267907187256,0.011393023405034543,"[0.7394993586264058, 9.536097798967883e-08, 2.68697271745604e-06, 0.0048229502529694825, 0.25567490878692944]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0Lr9HQijA1,Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations,Imprecise Label Learning,5.75,3.0,Hao Chen;Ankit Shah;Jindong Wang;Ran Tao;Yidong Wang;Xiang Li;Xing Xie;Masashi Sugiyama;Rita Singh;Bhiksha Raj,"Carnegie Mellon University;Accenture;Microsoft Research;Peking University;Microsoft Research Asia;The University of Tokyo;School of Computer Science, Carnegie Mellon University;Mohamed bin Zayed University of Artificial Intelligence",PhD student;Principal Researcher;Researcher;PhD student;Senior Principal Researcher;Full Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96933,,,https://openreview.net/forum?id=0Lr9HQijA1,/media/PosterPDFs/NeurIPS%202024/96933.png?t=1731704880.9846606
10,38,-0.06471333,0.08954511,4,-0.20931696028541216,-0.0035235230900599545,"[0.433220728081489, 5.350074499579003e-10, 0.0008329856552246833, 0.00022005794828601293, 0.5657262277799929]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0MXzbAv8xy,GFT: Graph Foundation Model with Transferable Tree Vocabulary,Graph Foundation Model;Transferability;Computation Tree;Graph Neural Network,6.0,3.75,Zehong Wang;Zheyuan Zhang;Nitesh V Chawla;Chuxu Zhang;Yanfang Ye,University of Notre Dame;University of Notre Dame;University of Notre Dame;University of Notre Dame,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96932,,,https://openreview.net/forum?id=0MXzbAv8xy,
10,39,0.06407858,0.09707585,0,0.06371267907187256,0.011393023405034543,"[0.9949395466011661, 7.230493743050073e-07, 4.522646918955518e-05, 0.00042353803367748175, 0.004590965846592517]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0NMzBwqaAJ,Not All Tokens Are What You Need for Pretraining,pre-training;next token prediction;data optimization;data selection,7.666666666666667,4.0,Zhenghao Lin;Zhibin Gou;Yeyun Gong;Xiao Liu;yelong shen;Ruochen Xu;Chen Lin;Yujiu Yang;Jian Jiao;Nan Duan;Weizhu Chen,Xiamen University;Microsoft;Microsoft Research Asia;Microsoft Research;Xiamen University;Tsinghua University;Microsoft;Microsoft Research Asia;Microsoft GenAI,MS student;Intern;Researcher;Researcher;Full Professor;Full Professor;Principal Researcher;Principal Researcher;Vice President,https://neurips.cc/virtual/2024/poster/96931,,,https://openreview.net/forum?id=0NMzBwqaAJ,/media/PosterPDFs/NeurIPS%202024/96931.png?t=1733724962.7310221
10,40,-0.021407472,0.09407413,0,0.06371267907187256,0.011393023405034543,"[0.8116934310194434, 7.911873135026542e-09, 0.0004914487325458318, 0.0003515348512046851, 0.18746357748493314]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0NQzQVu9tY,DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors,representation learning;offline reinforcement learning;behavioral cloning;visual distractor,7.0,3.0,Joseph Ortiz;Antoine Dedieu;Wolfgang Lehrach;J Swaroop Guntupalli;Carter Wendelken;Ahmad Humayun;Sivaramakrishnan Swaminathan;Guangyao Zhou;Miguel Lazaro-Gredilla;Kevin Patrick Murphy,Google DeepMind;Google DeepMind;Google Deepmind;Google DeepMind;Google;Google DeepMind;Google DeepMind;Google DeepMind;Google Deepmind;Google,Researcher;Researcher;Researcher;Researcher;Researcher;Researcher;Research Engineer;Research Scientist;Research Scientist;Principal Researcher,https://neurips.cc/virtual/2024/poster/97877,,,,/media/PosterPDFs/NeurIPS%202024/97877.png?t=1733266397.4133346
10,41,-0.056248758,0.025906589,0,0.06371267907187256,0.011393023405034543,"[0.5994903513335785, 3.05594405856205e-08, 4.901617847895547e-06, 0.003573620871512918, 0.3969310956176199]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0SMhqvgHST,EEVEE and GATE: Finding the right benchmarks and how to run them seamlessly,multi-modal;benchmarks;machine learning;model evaluation;benchmark frameworks,6.0,4.0,Antreas Antoniou;Eleni Triantafillou;Hugo Larochelle;Sebastien Montella;Fady Rezk;Kiyoon Kim;Linus Ericsson;Pavlos Vougiouklis;Justin Engelmann;Elliot J. Crowley;Srihari Humbarwadi;Yi Liu;Guang Yang;Jeff Z. Pan;Amos Storkey,"Google;Google;Huawei Technologies Ltd.;Samsung;Deargen;University of Edinburgh, University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh;Huawei Technologies Ltd.;University of Edinburgh, University of Edinburgh;University of Edinburgh",Researcher;Research Scientist;Researcher;Intern;Researcher;Postdoc;Researcher;Assistant Professor;Researcher;Full Professor;Full Professor,,,,,
10,42,-0.15132618,0.02146309,4,-0.20931696028541216,-0.0035235230900599545,"[0.05313104723612148, 2.543686925179846e-11, 1.082736898338743e-05, 0.00041041969570047577, 0.9464477056737578]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0SRJBtTNhX,IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors,Graph Machine Learning;Graph Data Augmentation;Graph Neural Networks,5.5,4.0,Shenghe Zheng;Hongzhi Wang;Xianglong Liu,Harbin Institute of Technology;Harbin Institute of Technology;Harbin Institute of Technology,MS student;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96930,,,https://openreview.net/forum?id=0SRJBtTNhX,/media/PosterPDFs/NeurIPS%202024/96930.png?t=1732617637.3891017
10,43,-0.18518934,0.0027779788,4,-0.20931696028541216,-0.0035235230900599545,"[0.024092462587654663, 5.3215281249456015e-12, 3.7768180575991608e-06, 0.0003944349246752169, 0.975509325664291]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0T8xRFrScB,Benchmarking Counterfactual Image Generation,benchmark;causal inference;counterfactual image generation,7.25,3.75,Thomas Melistas;Nikos Spyrou;Nefeli Gkouti;Pedro Sanchez;Athanasios Vlontzos;Yannis Panagakis;Giorgos Papanastasiou;Sotirios A. Tsaftaris,"University of Athens;University of Athens;University of Athens;University of Edinburgh, University of Edinburgh;Spotify;Pfizer;University of Edinburgh",PhD student;PhD student;PhD student;PhD student;Researcher;Principal Researcher;Professor in machine learning and computer vision,https://neurips.cc/virtual/2024/poster/97876,,,,/media/PosterPDFs/NeurIPS%202024/97876.png?t=1731712408.6398222
10,44,0.5118622,-0.024860546,1,0.4075643889177964,-0.08207163922598883,"[3.6539765722916664e-05, 0.999961184562571, 5.698933820917122e-20, 2.275671705919693e-06, 2.6632437559751077e-21]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0TUMAAb3of,Queueing Matching Bandits with Preference Feedback,Bandits;Queue;Preference Feedback,6.0,2.5,Jung-hun Kim;Min-hwan Oh,Seoul National University;Seoul National University,Assistant Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96929,,,https://openreview.net/forum?id=0TUMAAb3of,/media/PosterPDFs/NeurIPS%202024/96929.png?t=1733803835.532587
10,45,-0.0018669573,0.3644946,2,-0.09463330063911646,0.3327342704201369,"[0.0016288859926144096, 4.0781384339026255e-18, 0.9983573950474978, 8.509643551690741e-13, 1.3718959036788228e-05]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,0VeSCjRDBy,Adversarial Moment-Matching Distillation of Large Language Models,Knowledge distillation;Large language models;Imitation learning;Moment-matching;Adversarial training,6.25,3.0,Chen Jia,,,https://neurips.cc/virtual/2024/poster/96928,,,https://openreview.net/forum?id=0VeSCjRDBy,/media/PosterPDFs/NeurIPS%202024/96928.png?t=1731660620.7591212
10,46,-0.24925767,0.015651966,4,-0.20931696028541216,-0.0035235230900599545,"[0.004322614591072965, 1.576549618453956e-14, 2.781807645809469e-05, 5.0205380547534725e-05, 0.9955993619519057]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0WCFI2Qx85,ScaleKD: Strong Vision Transformers Could Be Excellent Teachers,knowledge distillation;model compression;training acceleration;vision transformer;convolutional neural network;multi-layer perception,6.25,4.5,Jiawei Fan;Chao Li;Xiaolong Liu;Anbang Yao,Intel Labs China;Intel;Intel,Research Intern;Researcher;Principal Researcher,https://neurips.cc/virtual/2024/poster/96927,,,https://openreview.net/forum?id=0WCFI2Qx85,/media/PosterPDFs/NeurIPS%202024/96927.png?t=1731695837.2500114
10,47,0.2804453,-0.1894261,1,0.4075643889177964,-0.08207163922598883,"[0.004891591645546284, 0.9896039998327716, 1.6019154901337956e-23, 0.005504408520630175, 1.052012178645687e-12]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0XKvW4ijxp,Learning-Augmented Algorithms with Explicit Predictors,online algorithms;learning-augmented algorithms;scheduling;caching,6.0,4.0,Marek Elias;Haim Kaplan;Yishay Mansour;Shay Moran,"Bocconi University;Technion, Technion;School of Computer Science, Tel Aviv University",Assistant Professor;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96926,,,https://openreview.net/forum?id=0XKvW4ijxp,/media/PosterPDFs/NeurIPS%202024/96926.png?t=1733319671.0065775
10,48,0.37225774,-0.11562894,1,0.4075643889177964,-0.08207163922598883,"[0.0009028170957706476, 0.9988111322121157, 1.7531306144206788e-21, 0.0002860506921122036, 1.4418608289911916e-15]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0XeNkkENuI,The Road Less Scheduled,Stochastic Optimization;Optimization;Convex Optimization;Learning Rates;Learning Rate Schedules,7.5,3.5,Aaron Defazio;Xingyu Alice Yang;Ahmed Khaled;Konstantin Mishchenko;Harsh Mehta;Ashok Cutkosky,Meta;Meta;Princeton University;Samsung;Google Research;Boston University,Research Scientist;Research Engineer;PhD student;Researcher;Software Engineer;Assistant Professor,https://neurips.cc/virtual/2024/poster/96925,,,https://openreview.net/forum?id=0XeNkkENuI,/media/PosterPDFs/NeurIPS%202024/96925.png?t=1730837481.9895687
10,49,0.1460578,0.21914145,0,0.06371267907187256,0.011393023405034543,"[0.9829185937541155, 1.1319215032105876e-07, 0.01703845034169083, 2.628924996964071e-06, 4.0213787046318644e-05]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0ZZMUjZJYF,Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study,LLMs;Learning by Teaching;Reasoning;Mathematical Reasoning;Code Synthesis;Weak-to-Strong Generalization;In-Context Learning;Prompting;Knowledge Distillation;Education-Inspired,6.5,4.0,Xuefei Ning;Zifu Wang;Shiyao Li;Zinan Lin;Peiran Yao;Tianyu Fu;Matthew B. Blaschko;Guohao Dai;Huazhong Yang;Yu Wang,Tsinghua University;KU Leuven;Tsinghua University;Microsoft;Infinigence;Shanghai Jiaotong University;Tsinghua University;Tsinghua University;KU Leuven,Research Assistant Professor;PhD student;PhD student;Senior Researcher;Researcher;Associate Professor;Full Professor;Full Professor;Associate Professor,https://neurips.cc/virtual/2024/poster/96924,,,https://openreview.net/forum?id=0ZZMUjZJYF,/media/PosterPDFs/NeurIPS%202024/96924.png?t=1732367562.4969194
10,50,0.07159563,-0.024327766,0,0.06371267907187256,0.011393023405034543,"[0.9691566038266615, 0.00023240833800722667, 7.846850940003169e-10, 0.029351734229326663, 0.0012592528213197112]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0ZeONp33f0,Graph Neural Networks and Arithmetic Circuits,Machine Learning;Graph Neural Networks;Arithmetic Circuits;Computational Complexity,6.5,3.25,Timon Barlag;Vivian Holzapfel;Laura Strieker;Jonni Virtema;Heribert Vollmer,Universität Hannover;Leibniz Universität Hannover;Leibniz Universität Hannover;University of Sheffield;Leibniz Universität Hannover,PhD student;Undergrad student;PhD student;Lecturer;Full Professor,https://neurips.cc/virtual/2024/poster/96923,,,https://openreview.net/forum?id=0ZeONp33f0,/media/PosterPDFs/NeurIPS%202024/96923.png?t=1732106485.9402945
10,51,-0.078428976,-0.18954016,3,-0.12517292191148427,-0.27255963411007533,"[0.252991708891411, 4.83383372453514e-05, 8.467485369417657e-16, 0.7378344834330122, 0.009125469338330765]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,0aN7VWwp4g,Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting,Precipitation Nowcasting;Video Prediction;Fourier Analysis;Loss Function,6.0,4.0,Chiu-Wai Yan;Shi Quan Foo;Van-Hoan Trinh;Dit-Yan Yeung;Ka-Hing Wong;Wai-Kin Wong,Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology,Chair Professor;Researcher;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96922,,,https://openreview.net/forum?id=0aN7VWwp4g,/media/PosterPDFs/NeurIPS%202024/96922.png?t=1731480203.951872
10,52,-0.23586994,0.37846398,2,-0.09463330063911646,0.3327342704201369,"[1.2612795576168407e-06, 1.9690513498551223e-28, 0.9999778180686226, 9.768515791387167e-17, 2.0920651819850847e-05]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,0bFXbEMz8e,FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions,generative models;material generation;chemistry;flow matching;large language models,6.0,4.333333333333333,Anuroop Sriram;Benjamin Kurt Miller;Ricky T. Q. Chen;Brandon M Wood,"Meta Facebook;University of Amsterdam;FAIR at Meta;FAIR Labs, Meta AI",Principal Researcher;PhD student;Researcher;Researcher,https://neurips.cc/virtual/2024/poster/96921,,,https://openreview.net/forum?id=0bFXbEMz8e,/media/PosterPDFs/NeurIPS%202024/96921.png?t=1730973273.143089
10,53,-0.15925287,-0.015642455,4,-0.20931696028541216,-0.0035235230900599545,"[0.06031576327417865, 1.3243441895264898e-10, 6.47260960238723e-07, 0.0018080268842559036, 0.9378755624481708]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0bINeW40u4,Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning,Medical Multi-modal Alignment;Eye-gaze;Radiology,6.25,3.5,Chong Ma;Hanqi Jiang;Wenting Chen;Yiwei Li;Zihao Wu;Xiaowei Yu;Zhengliang Liu;Lei Guo;Dajiang Zhu;Tuo Zhang;Dinggang Shen;Tianming Liu;Xiang Li,"Northwest Polytechnical University Xi'an;Beijing Jiaotong University;City University of Hong Kong;University of Georgia;University of Georgia;University of Texas at Arlington, University of Texas at Arlington;University of Georgia;University of Texas at Arlington;Northwestern Polytechnical University;ShanghaiTech University;University of Georgia;Massachusetts General Hospital, Harvard University",PhD student;Undergrad student;PhD student;PhD student;PhD student;PhD student;PhD student;Assistant Professor;Associate Professor;Full Professor;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96920,,,https://openreview.net/forum?id=0bINeW40u4,
10,54,0.38273144,-0.19184409,1,0.4075643889177964,-0.08207163922598883,"[0.00014075666165641696, 0.9997066572635904, 1.1203478133195305e-26, 0.000152586074752974, 1.663633017631664e-17]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0cSQ1Sg7db,Generalization of Hamiltonian algorithms,Generalization;stochastic algorithms;concentration inequalities;PAC-Bayes,6.5,3.0,Andreas Maurer,,,https://neurips.cc/virtual/2024/poster/96919,,,https://openreview.net/forum?id=0cSQ1Sg7db,
10,55,-0.029614072,-0.05991212,0,0.06371267907187256,0.011393023405034543,"[0.8482254751350214, 8.21452925037339e-06, 7.944790735615855e-10, 0.08262538970448388, 0.0691409198367652]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0cgDDa4OFr,Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation,source distribution estimation;maximum entropy;Sliced-Wasserstein distance;empirical Bayes;simulation-based inference,5.8,2.8,Julius Vetter;Guy Moss;Cornelius Schröder;Richard Gao;Jakob H. Macke,Eberhard-Karls-Universität Tübingen;Eberhard-Karls-Universität Tübingen;University Tübingen;Eberhard-Karls-Universität Tübingen,PhD student;PhD student;Postdoc;Postdoc,https://neurips.cc/virtual/2024/poster/96918,,,https://openreview.net/forum?id=0cgDDa4OFr,/media/PosterPDFs/NeurIPS%202024/96918.png?t=1733318904.6928847
10,56,-0.041920777,-0.1336057,0,0.06371267907187256,0.011393023405034543,"[0.5676944616383354, 6.324541404346476e-05, 3.0673347766670886e-13, 0.41296599358371827, 0.019276299363596167]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0d50Il6enG,Non-parametric classification via expand-and-sparsify representation,non-parametric regression;non-parametric classification;expand-and-sparsify representation;universal consistency;minimax-optimal convergence rate,6.0,3.0,Kaushik Sinha,Wichita State University,Associate Professor,https://neurips.cc/virtual/2024/poster/96917,,,https://openreview.net/forum?id=0d50Il6enG,/media/PosterPDFs/NeurIPS%202024/96917.png?t=1731697679.5420048
10,57,-0.05421332,-0.22073112,3,-0.12517292191148427,-0.27255963411007533,"[0.17204234424852824, 0.00026586233713936646, 4.08647984672954e-18, 0.8266656363645827, 0.0010261570497495278]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,0dtA21q83C,DeNetDM: Debiasing by Network Depth Modulation,Trustworthy Machine Learning;Debiasing;Robustness,6.0,3.5,Silpa Vadakkeeveetil Sreelatha;Adarsh Kappiyath;Abhra Chaudhuri;Anjan Dutta,University of Surrey;University of Exeter;University of Surrey,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96916,,,https://openreview.net/forum?id=0dtA21q83C,/media/PosterPDFs/NeurIPS%202024/96916.png?t=1733689557.490417
10,58,-0.19589648,0.09422963,4,-0.20931696028541216,-0.0035235230900599545,"[0.010205781885086921, 7.233334932021448e-15, 0.00339351624847396, 4.331612932675873e-06, 0.9863963702534994]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0e5uOaJxo1,Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure,Graph Neural Network;Protein Sequence;Structure,5.0,3.3333333333333335,Bozhen Hu;Cheng Tan;Jun Xia;Yue Liu;Lirong Wu;Jiangbin Zheng;Yongjie Xu;Yufei Huang;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University, China;National University of Singapore;Westlake University;Westlake University;Westlake University;Zhejiang University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96915,,,https://openreview.net/forum?id=0e5uOaJxo1,/media/PosterPDFs/NeurIPS%202024/96915.png?t=1730385968.8958924
10,59,0.09615892,0.18102637,0,0.06371267907187256,0.011393023405034543,"[0.9926188088746646, 5.574325445708043e-08, 0.006575222821098407, 1.2895754942874908e-05, 0.000793016806039726]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0feJEykDRx,Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models,spatial-temporal data mining;location-based service;check-in sequence;large language model,5.75,4.0,Letian Gong;Yan Lin;Xinyue Zhang;Yiwen Lu;Xuedi Han;Yichen Liu;Shengnan Guo;Youfang Lin;Huaiyu Wan,Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University;Beijing Jiaotong University,PhD student;PhD student;Undergrad student;Undergrad student;MS student;Associate Professor;Full Professor;Full Professor;Undergrad student,https://neurips.cc/virtual/2024/poster/96914,,,https://openreview.net/forum?id=0feJEykDRx,/media/PosterPDFs/NeurIPS%202024/96914.png?t=1731289337.5941467
10,60,-0.013711061,-0.07216554,0,0.06371267907187256,0.011393023405034543,"[0.8551578350488218, 2.8884449156520035e-05, 1.234687983082364e-10, 0.1155334039299263, 0.02927987644862642]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0jld45XGgJ,Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?,neural collapse;deep neural collapse;unconstrained features model;deep unconstrained features model;low-rank bias,6.5,3.75,Peter Súkeník;Christoph H. Lampert;Marco Mondelli,Institute of Science and Technology;Institute of Science and Technology Austria;Institute of Science and Technology Austria,PhD student;Assistant Professor;Professor,https://neurips.cc/virtual/2024/poster/96913,,,https://openreview.net/forum?id=0jld45XGgJ,
10,61,0.49365819,-0.019841706,1,0.4075643889177964,-0.08207163922598883,"[8.215960121538876e-05, 0.9999135758664314, 3.4797686257378947e-19, 4.26453235332507e-06, 3.13794179374161e-20]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0l9yGPTHAU,Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms,Robust Markov decision process;norm;sample complexity;strong duality,6.5,3.0,Pierre Clavier;Laixi Shi;Erwan Le Pennec;Eric Mazumdar;Adam Wierman;Matthieu Geist,"École Polytechnique;California Institute of Technology;Ecole polytechnique;Deparment of Computing + Mathematical Sciences, California Institute of Technology;California Institute of Technology;Google",PhD student;Postdoc;Full Professor;Assistant Professor;Professor;Researcher,https://neurips.cc/virtual/2024/poster/96912,,,https://openreview.net/forum?id=0l9yGPTHAU,
10,62,-0.096782275,0.2680031,2,-0.09463330063911646,0.3327342704201369,"[0.003940997639782145, 1.697048495871276e-17, 0.988936073354615, 3.626638908367665e-10, 0.007122928642938785]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,0lBx844upd,ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models,network pruning;unstructured pruning;large language model;ADMM;pre-conditioned conjugate gradient;optimization,5.333333333333333,3.0,Xiang Meng;Kayhan Behdin;Haoyue Wang;Rahul Mazumder,Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology,PhD student;PhD student;PhD student;Associate Professor,https://neurips.cc/virtual/2024/poster/96911,,,https://openreview.net/forum?id=0lBx844upd,/media/PosterPDFs/NeurIPS%202024/96911.png?t=1731079283.0533488
10,63,-0.07022652,-0.30347943,3,-0.12517292191148427,-0.27255963411007533,"[0.052052391695808005, 0.0005784164444714078, 3.534154258901066e-23, 0.9473311293657017, 3.806249401876773e-05]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,0lau89u4oE,Accelerating Non-Maximum Suppression: A Graph Theory Perspective,non-maximum suppression;object detection;graph theory,5.5,3.25,King-Siong Si;Lu Sun;Weizhan Zhang;Tieliang Gong;Jiahao Wang;Jiang Liu;Hao Sun,Xi'an Jiaotong University;Xi'an Jiaotong University;North China University of Technology;China Telecom Corporation Ltd. Data&AI Technology Company,MS student;MS student;MS student;Researcher,https://neurips.cc/virtual/2024/poster/96910,,,https://openreview.net/forum?id=0lau89u4oE,/media/PosterPDFs/NeurIPS%202024/96910.png?t=1733315333.5240822
10,64,-0.08510746,-0.26066056,3,-0.12517292191148427,-0.27255963411007533,"[0.08372951832270739, 0.0001418176629723746, 4.104068905328104e-20, 0.9156604106597852, 0.0004682533545350526]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,0m19blQT6y,BitsFusion: 1.99 bits Weight Quantization of Diffusion Model,Diffusion;Quantization;Stable Diffusion;Low bit,5.75,4.5,Yang Sui;Yanyu Li;Anil Kag;Yerlan Idelbayev;Junli Cao;Ju Hu;Dhritiman Sagar;Bo Yuan;Sergey Tulyakov;Jian Ren,Rutgers University;Northeastern University;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Snap Inc.;Rutgers University;Snap Inc.;Snap Inc.,PhD student;PhD student;Researcher;Researcher;Researcher;Researcher;Researcher;Assistant Professor;Director of Research;Research Scientist,https://neurips.cc/virtual/2024/poster/96909,,,https://openreview.net/forum?id=0m19blQT6y,/media/PosterPDFs/NeurIPS%202024/96909.png?t=1729915675.3170154
10,65,-0.00251228,0.3769304,2,-0.09463330063911646,0.3327342704201369,"[0.0011079086312243116, 1.1294881686936174e-18, 0.9988847192440058, 2.703831398913908e-13, 7.3721244995650025e-06]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,0mRouJElbZ,ProgressGym: Alignment with a Millennium of Moral Progress,Progress Alignment;AI Alignment;Large Language Models,7.666666666666667,2.6666666666666665,Tianyi Qiu;Yang Zhang;Xuchuan Huang;Jasmine Xinze Li;Jiaming Ji;Yaodong Yang,"University of California, Berkeley;Peking University;Peking University;Peking University;Peking University;Peking University",Intern;Undergrad student;Undergrad student;Intern;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/97875,,,,/media/PosterPDFs/NeurIPS%202024/97875.png?t=1731742041.9348912
10,66,0.42614552,0.08994585,1,0.4075643889177964,-0.08207163922598883,"[0.02865436951734678, 0.9712972435972602, 3.109376545134919e-11, 4.838685429213116e-05, 7.161650990840882e-15]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0nSY8NiILP,Tight Bounds for Learning RUMs from Small Slates,discrete choice;random utility model;approximation theory,6.0,2.75,Flavio Chierichetti;Mirko Giacchini;Ravi Kumar;Alessandro Panconesi;Andrew Tomkins,Sapienza University of Rome;Sapienza University of Rome;Google;Sapienza University of Rome;Google,Full Professor;PhD student;Research Scientist;Full Professor;Researcher,https://neurips.cc/virtual/2024/poster/96908,,,https://openreview.net/forum?id=0nSY8NiILP,/media/PosterPDFs/NeurIPS%202024/96908.png?t=1732698791.0319488
10,67,0.25132486,-0.20319358,1,0.4075643889177964,-0.08207163922598883,"[0.010016695876827852, 0.9756243873569157, 1.461241415159045e-23, 0.014358916755820992, 1.0435417135071116e-11]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0nzKznCjFG,Private and Personalized Frequency Estimation in a Federated Setting,federated learning;personalization;privacy,5.75,3.0,Amrith Setlur;Vitaly Feldman;Kunal Talwar,Carnegie Mellon University;Apple AI Research;Apple,PhD student;Research Scientist;Research Scientist,https://neurips.cc/virtual/2024/poster/96907,,,https://openreview.net/forum?id=0nzKznCjFG,
10,68,-0.18157998,0.03947093,4,-0.20931696028541216,-0.0035235230900599545,"[0.019522475402859882, 7.088411653521738e-13, 5.7769175737697224e-05, 7.889110268824594e-05, 0.9803408643180052]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0o7Rd5jngV,Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling,Transformer;expressive power;theoretical insights,6.333333333333333,3.0,Mingze Wang;Weinan E,Peking University;Peking University,PhD student;Full Professor,https://neurips.cc/virtual/2024/poster/96906,,,https://openreview.net/forum?id=0o7Rd5jngV,
10,69,-0.12251995,-0.049827244,4,-0.20931696028541216,-0.0035235230900599545,"[0.2403767818473365, 1.7663506938673038e-08, 2.355116116191446e-08, 0.020734030646191535, 0.7388891462918039]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0o9E8AsFgW,DarkSAM: Fooling Segment Anything Model to Segment Nothing,Segment Anything Model;Adversarial Example,6.333333333333333,4.0,Ziqi Zhou;Yufei Song;Minghui Li;Shengshan Hu;Xianlong Wang;Leo Yu Zhang;Dezhong Yao;Hai Jin,Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology;Griffith University;Huazhong University of Science and Technology;Huazhong University of Science and Technology,PhD student;PhD student;Assistant Professor;Associate Professor;PhD student;Researcher;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96905,,,https://openreview.net/forum?id=0o9E8AsFgW,
10,70,-0.18423451,0.25213403,2,-0.09463330063911646,0.3327342704201369,"[0.00046537189805339685, 2.5551989571911264e-20, 0.9831433375707982, 8.268009289656894e-11, 0.016391290448468564]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,0oUutV92YF,ProtGO: Function-Guided Protein Modeling for Unified Representation Learning,Teacher-student;Knowledge Distillation;Protein Function,5.666666666666667,3.6666666666666665,Bozhen Hu;Cheng Tan;Yongjie Xu;Zhangyang Gao;Jun Xia;Lirong Wu;Stan Z. Li,"Westlake University;Zhejiang University & Westlake University;Westlake University;Westlake University, China;Westlake University, China;Westlake University;Westlake University",PhD student;PhD student;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96904,,,https://openreview.net/forum?id=0oUutV92YF,/media/PosterPDFs/NeurIPS%202024/96904.png?t=1730386167.5899446
10,71,-0.04843812,0.4040603,2,-0.09463330063911646,0.3327342704201369,"[0.0001646781130296688, 1.199817934121588e-21, 0.9998313133081641, 5.686818747120255e-15, 4.008578800612875e-06]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,0og7nmvDbe,Confidence Regulation Neurons in Language Models,LLMs;Interpretability;Mechanistic Interpretability,7.0,3.75,Alessandro Stolfo;Ben Peng Wu;Wes Gurnee;Yonatan Belinkov;Xingyi Song;Mrinmaya Sachan;Neel Nanda,"ETHZ - ETH Zurich;University of Sheffield;Massachusetts Institute of Technology;Technion, Technion;University of Sheffield;Google DeepMind;Swiss Federal Institute of Technology",PhD student;PhD student;PhD student;Assistant Professor;Lecturer;Researcher;Assistant Professor,https://neurips.cc/virtual/2024/poster/96903,,,https://openreview.net/forum?id=0og7nmvDbe,
10,72,0.25011468,-0.18353273,1,0.4075643889177964,-0.08207163922598883,"[0.01610872251383174, 0.9667311835477693, 3.2621628590166197e-22, 0.0171600939075041, 3.0894892526394325e-11]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0qb8KoPsej,Accelerating Matroid Optimization through Fast Imprecise Oracles,matroid optimization;weak-strong models;learning-augmented algorithms;algorithms with predictions;query minimization;robustness,5.5,2.75,Franziska Eberle;Felix Hommelsheim;Alexander Lindermayr;Zhenwei Liu;Nicole Megow;Jens Schlöter,Technische Universität Berlin;Universität Bremen;Universität Bremen;Universität Bremen;Universität Bremen,Postdoc;Postdoc;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96902,,,https://openreview.net/forum?id=0qb8KoPsej,
10,73,0.24778247,-0.18444899,1,0.4075643889177964,-0.08207163922598883,"[0.017116025117954146, 0.9643270033120859, 3.3383312722882076e-22, 0.0185569715326141, 3.734597140147568e-11]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0rl5vWOzRU,Score-Optimal Diffusion Schedules,Diffusion model;adaptive schedule;Annealed Langevin,6.0,3.0,Christopher Williams;Andrew Campbell;Arnaud Doucet;Saifuddin Syed,University of Oxford;University of Oxford;University of Oxford;University of Oxford,PhD student;PhD student;Full Professor;Postdoc,https://neurips.cc/virtual/2024/poster/96901,,,https://openreview.net/forum?id=0rl5vWOzRU,
10,74,-0.17648138,-0.41862112,3,-0.12517292191148427,-0.27255963411007533,"[0.009162290890067754, 5.595518971409896e-05, 3.3092217724739107e-29, 0.9907797565385806, 1.997381637416804e-06]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,0sJBW05a2W,3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration,Point Cloud Registration;Focus and Matching,5.666666666666667,4.333333333333333,Liyuan Zhang;Le Hui;qi liu;Bo Li;Yuchao Dai,Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwest Polytechnical University Xi'an;Northwestern Polytechnical University Xi'an;Northwestern Polytechnical University,MS student;Associate Professor;Researcher;Associate Professor;Professor,https://neurips.cc/virtual/2024/poster/96900,,,https://openreview.net/forum?id=0sJBW05a2W,/media/PosterPDFs/NeurIPS%202024/96900.png?t=1731333373.8074756
10,75,-0.16704087,-0.3598848,3,-0.12517292191148427,-0.27255963411007533,"[0.015217028352141856, 2.5202620432786737e-05, 2.8365312205055107e-25, 0.9847249672126698, 3.2801814755614416e-05]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,0sycTGl4In,4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization,Dynamic Novel View Synthesis;4D Gaussian splatting;Sparse reconstruction;in-the-wild,5.333333333333333,4.666666666666667,Mijeong Kim;Jongwoo Lim;Bohyung Han,Seoul National University;Seoul National University,Full Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96899,,,https://openreview.net/forum?id=0sycTGl4In,/media/PosterPDFs/NeurIPS%202024/96899.png?t=1733712090.5881364
10,76,0.61073065,0.018717432,1,0.4075643889177964,-0.08207163922598883,"[2.1629402563801158e-06, 0.9999977659998053, 3.842124063755495e-20, 7.105993838287831e-08, 2.652140498127288e-26]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,0uGlKYS7a2,Maximizing utility in multi-agent environments by anticipating the behavior of other learners,Game Theory; no regret; learning theory;,5.5,3.25,Angelos Assos;Yuval Dagan;Constantinos Costis Daskalakis,Massachusetts Institute of Technology;Massachusetts Institute of Technology,MS student;Full Professor,https://neurips.cc/virtual/2024/poster/96898,,,https://openreview.net/forum?id=0uGlKYS7a2,/media/PosterPDFs/NeurIPS%202024/96898.png?t=1731753379.9098587
10,77,-0.07488669,0.3827278,2,-0.09463330063911646,0.3327342704201369,"[0.00013492500657783855, 8.044553222168197e-22, 0.9998501156752739, 1.573397464378482e-14, 1.4959318132565844e-05]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,0uXtFk5KNJ,BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models,block coordinate descent;large language models,5.25,3.75,Qijun Luo;Hengxu Yu;Xiao Li,"The Chinese University of Hong Kong, Shenzhen;The Chinese University of Hong Kong, Shenzhen;Chinese University of Hong Kong Shen Zhen",PhD student;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96897,,,https://openreview.net/forum?id=0uXtFk5KNJ,/media/PosterPDFs/NeurIPS%202024/96897.png?t=1733743857.9232197
10,78,0.022653038,0.24370801,2,-0.09463330063911646,0.3327342704201369,"[0.31803578372058067, 8.288247023990909e-12, 0.6761495838413257, 1.5657439530860355e-07, 0.005814475855410005]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,0zFVhMBZHJ,Mixture of Tokens: Continuous MoE through Cross-Example Aggregation,LLM;Mixture of Experts;MoE;conditional computation;fully-differentiable;language modeling,6.0,3.6666666666666665,Szymon Antoniak;Michał Krutul;Maciej Pióro;Jakub Krajewski;Jan Ludziejewski;Kamil Ciebiera;Krystian Król;Tomasz Odrzygóźdź;Marek Cygan;Sebastian Jaszczur,IDEAS NCBR Sp.;IDEAS NCBR Sp.;University of Warsaw;University of Warsaw;IDEAS NCBR Sp.;University of Warsaw;IDEAS NCBR;Nomagic;University of Warsaw,PhD student;Researcher;PhD student;PhD student;Intern;MS student;Postdoc;Founder / CTO;PhD student,https://neurips.cc/virtual/2024/poster/96896,,,https://openreview.net/forum?id=0zFVhMBZHJ,/media/PosterPDFs/NeurIPS%202024/96896.png?t=1730308223.324062
10,79,0.24368975,0.18879418,0,0.06371267907187256,0.011393023405034543,"[0.9996840902951838, 9.808975743680475e-05, 0.0002013376598538593, 1.6349824813059282e-05, 1.3246271240236071e-07]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,0zWzJj6lO3,Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents,cooperative AI;AI safety;LLM agents;cognitive science;language model evaluation;dynamic evaluation;alignment;agency;evolving benchmarks;multi-agent interactions,5.75,3.5,Giorgio Piatti;Zhijing Jin;Max Kleiman-Weiner;Bernhard Schölkopf;Mrinmaya Sachan;Rada Mihalcea,Common Sense Machines;University of Michigan;Swiss Federal Institute of Technology,Principal Researcher;Full Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96895,,,https://openreview.net/forum?id=0zWzJj6lO3,
10,80,-0.16938657,-0.05973538,4,-0.20931696028541216,-0.0035235230900599545,"[0.07907080586456872, 9.42832027549865e-10, 1.9974177924739288e-08, 0.010557992535470177, 0.9103711806829511]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,0zfUiSX5si,AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases,De Novo Peptide sequencing;Proteomics;Mass Spectrum,5.333333333333333,3.0,Jun Xia;Shaorong Chen;Jingbo Zhou;Xiaojun Shan;Wenjie Du;Zhangyang Gao;Cheng Tan;Bozhen Hu;Jiangbin Zheng;Stan Z. Li,"Westlake University, China;Westlake University;Jilin University;University of Electronic Science and Technology of China;University of Science and Technology of China;Westlake University, China;Zhejiang University & Westlake University;Westlake University;Westlake University;Westlake University",PhD student;PhD student;Undergrad student;Undergrad student;Assistant Professor;PhD student;PhD student;PhD student;PhD student;Chair Professor,https://neurips.cc/virtual/2024/poster/96894,,,https://openreview.net/forum?id=0zfUiSX5si,
10,81,-0.25151917,-0.28693447,3,-0.12517292191148427,-0.27255963411007533,"[0.02056881618447986, 1.1071463988212962e-07, 7.602951480044135e-19, 0.9730712961953552, 0.006359776905525158]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,105ZuvpdyW,SegVol: Universal and Interactive Volumetric Medical Image Segmentation,Volumetric Medical Image Segmentation;3D Segmentation Foundation Model;Universal and Interactive 3D Segmentation,7.666666666666667,4.333333333333333,Yuxin Du;Fan BAI;Tiejun Huang;Bo Zhao,Beijing Academy of Artificial Intelligence;The Chinese University of Hong Kong;Peking University;BAAI,Intern;PhD student;Full Professor;Principal Researcher,https://neurips.cc/virtual/2024/poster/96893,,,https://openreview.net/forum?id=105ZuvpdyW,/media/PosterPDFs/NeurIPS%202024/96893.png?t=1731410503.871179
10,82,0.04577409,-0.24324691,3,-0.12517292191148427,-0.27255963411007533,"[0.17524950264643074, 0.02626071223263231, 3.1733792027434434e-21, 0.7984830700355646, 6.7150853724772245e-06]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,1067784F6e,Data Distribution Valuation,Data distribution valuation;Huber model;Maximum mean discrepancy,6.333333333333333,4.333333333333333,Xinyi Xu;Shuaiqi Wang;Chuan-Sheng Foo;Bryan Kian Hsiang Low;Giulia Fanti,"National University of Singapore;Carnegie Mellon University;Institute for Infocomm Research, A*STAR;National University of Singapore;Carnegie Mellon University",PhD student;PhD student;Principal Scientist;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96892,,,https://openreview.net/forum?id=1067784F6e,/media/PosterPDFs/NeurIPS%202024/96892.png?t=1731176029.7581189
10,83,-0.22563006,-0.049784996,4,-0.20931696028541216,-0.0035235230900599545,"[0.01615557674566778, 7.059065648511603e-12, 1.1370989138768773e-07, 0.0018520302443011604, 0.9819922792930805]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,12A1RT1L87,Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?,Dataset Condensation;Dataset Distillation,5.666666666666667,3.6666666666666665,Lingao Xiao;Yang He,"School of Computer Science and  Engineering, Nanyang Technological University;Institute of High Performance Computing, Singapore, A*STAR",Undergrad student;Researcher,https://neurips.cc/virtual/2024/poster/96891,,,https://openreview.net/forum?id=12A1RT1L87,/media/PosterPDFs/NeurIPS%202024/96891.png?t=1731138766.8349779
10,84,-0.20074943,0.040258985,4,-0.20931696028541216,-0.0035235230900599545,"[0.01156423774229278, 1.4326172879639475e-13, 7.76946425485e-05, 4.6613209726481044e-05, 0.988311454405289]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,135eKqDoRR,Bayesian-guided Label Mapping for Visual Reprogramming,visual reprogramming;adversarial reprogramming;output label mapping;Bayesian probability,7.25,4.0,Chengyi Cai;Zesheng Ye;Lei Feng;Jianzhong Qi;Feng Liu,University of Melbourne;Singapore University of Technology and Design;University of Melbourne;University of Melbourne,PhD student;Assistant Professor;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96890,,,https://openreview.net/forum?id=135eKqDoRR,
10,85,-0.1496939,0.30529067,2,-0.09463330063911646,0.3327342704201369,"[0.00016596625500763578, 1.969592729404096e-21, 0.9987985644267066, 1.5755489062101274e-12, 0.001035469316710303]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,14hLJr6kZ3,Enhancing Domain Adaptation through Prompt Gradient Alignment,transfer learning; domain adaptation; prompt-tuning,6.25,3.25,Hoang Phan;Tung Lam Tran;Quyen Tran;Trung Le,VinAi Research;VinAI Research;Monash University;New York University,Research resident;Research Resident;Assistant Professor;PhD student,https://neurips.cc/virtual/2024/poster/96889,,,https://openreview.net/forum?id=14hLJr6kZ3,/media/PosterPDFs/NeurIPS%202024/96889.png?t=1732036918.0147438
10,86,0.2630342,0.051892787,0,0.06371267907187256,0.011393023405034543,"[0.9214983197096015, 0.07542603935633181, 2.3126753146077438e-09, 0.0030756054042097433, 3.321718172384108e-08]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,15460JjocO,Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners,multi-agent;reinforcement learning;robustness;diversity;specialization,7.0,3.6666666666666665,Rujikorn Charakorn;Poramate Manoonpong;Nat Dilokthanakul,Sakana AI;Vidyasirimedhi Institute of Science and Technology;King Mongkut's Institute of Technology Ladkrabang,Intern;Full Professor;Lecturer,https://neurips.cc/virtual/2024/poster/96888,,,https://openreview.net/forum?id=15460JjocO,/media/PosterPDFs/NeurIPS%202024/96888.png?t=1731395258.7214391
10,87,0.61719507,-0.024593957,1,0.4075643889177964,-0.08207163922598883,"[7.431634561035536e-07, 0.9999991872334262, 1.0224231882706633e-22, 6.960311776018608e-08, 3.0515713219004117e-27]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,15Jm9v7wCo,No-Regret Learning for Fair Multi-Agent Social Welfare Optimization,Online Learning;Nash Social Welfare,5.666666666666667,3.3333333333333335,Mengxiao Zhang;Ramiro Deo-Campo Vuong;Haipeng Luo,University of Southern California;University of Southern California,Undergrad student;Associate Professor,https://neurips.cc/virtual/2024/poster/96887,,,https://openreview.net/forum?id=15Jm9v7wCo,
10,88,-0.14552048,-0.15470643,3,-0.12517292191148427,-0.27255963411007533,"[0.2755802782795574, 7.349556601898409e-07, 1.036278780008419e-12, 0.48559991032291483, 0.23881907644083136]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,15PS30UOUp,Kuro Siwo: 33 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping,Synthetic Aperture Radar;SAR;Deep Learning;Remote Sensing;Floods;dataset,6.75,3.75,Nikolaos Ioannis Bountos;Maria Sdraka;Angelos Zavras;Andreas Karavias;Ilektra Karasante;Themistocles Herekakis;Angeliki Thanasou;Dimitrios Michail;Ioannis Papoutsis,National Observatory of Athens;National Observatory of Athens;Harokopio University;The Centre for Research & Technology;National Observatory of Athens ;National Observatoty of Athens;National Observatory of Athens;Harokopio University;National Technical University of Athens,PhD student;Researcher;PhD student;Researcher;Researcher;Researcher;Researcher;Associate Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/97874,,,,
10,89,0.004352061,-0.07103703,0,0.06371267907187256,0.011393023405034543,"[0.8749623147064343, 6.43246305478148e-05, 7.154855687777923e-11, 0.11108996345129316, 0.013883397140176286]","[0.013506689725134342, 0.015791936179500293]",0.21805869701618016,164QnJsYjF,Dense Associative Memory Through the Lens of Random Features,Associative Memory;Kernels;Random Features;Hopfield Network,6.0,3.0,Benjamin Hoover;Duen Horng Chau;Hendrik Strobelt;Parikshit Ram;Dmitry Krotov,International Business Machines;International Business Machines;International Business Machines;Massachusetts Institute of Technology;Georgia Institute of Technology,AI Research Engineer;Principal Researcher;Principal Researcher;Researcher;Full Professor,https://neurips.cc/virtual/2024/poster/96886,,,https://openreview.net/forum?id=164QnJsYjF,/media/PosterPDFs/NeurIPS%202024/96886.png?t=1733846086.053208
10,90,-0.31772932,0.41427824,2,-0.09463330063911646,0.3327342704201369,"[4.7584968615440185e-08, 1.2235766100269037e-33, 0.9999981989753195, 2.50362051689921e-19, 1.7534397121122955e-06]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,168NLzTpw8,Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation,Vision-Language;Region-Level Understanding;Multimodal Large Language Model,5.75,3.75,Yaoyuan Liang;Zhuojun Cai;Jian Xu;Guanbo Huang;Yiran Wang;Xiao Liang;Jiahao Liu;Ziran Li;Jingang Wang;Shao-Lun Huang,"Tsinghua Shenzhen International Graduate School, Tsinghua University;Microsoft;University of Electronic Science and Technology of China;Tsinghua University;Tsinghua University;Meituan;Meituan;Tsinghua University",PhD student;Intern;Undergrad student;MS student;MS student;Researcher;Researcher;Associate Professor,https://neurips.cc/virtual/2024/poster/96885,,,https://openreview.net/forum?id=168NLzTpw8,
10,91,-0.118134014,0.26676714,2,-0.09463330063911646,0.3327342704201369,"[0.0021261430173451653, 2.653553694457908e-18, 0.9896906272901701, 1.9705955285434547e-10, 0.008183229495425182]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,181llen2gw,A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks,Vision-Language Model;Fairness;Debias,6.333333333333333,3.6666666666666665,Hoin Jung;Taeuk Jang;Xiaoqian Wang,Purdue University;Purdue University;Purdue University,PhD student;PhD student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96884,,,https://openreview.net/forum?id=181llen2gw,/media/PosterPDFs/NeurIPS%202024/96884.png?t=1731379505.2628894
10,92,-0.19037005,0.30377576,2,-0.09463330063911646,0.3327342704201369,"[4.77154970833031e-05, 4.5605006969595694e-23, 0.9989501495431763, 4.399447996738083e-13, 0.0010021349593003835]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,18FGRNd0wZ,Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation,tokenization of crystals;language models;materials generation,6.0,3.5,Keqiang Yan;Xiner Li;Hongyi Ling;Kenna Ashen;Carl Edwards;Raymundo Arroyave;Marinka Zitnik;Heng Ji;Xiaofeng Qian;Xiaoning Qian;Shuiwang Ji,"Texas A&M University;Texas A&M University - College Station;Texas A&M University - College Station;Texas A&M University - College Station;Genentech;Texas A&M University Main Campus;Harvard University;University of Illinois, Urbana-Champaign;Texas A&M University;Texas A&M;Texas A&M University",PhD student;PhD student;PhD student;PhD student;Intern;Assistant Professor;Full Professor;Associate Professor;Full Professor;Professor,https://neurips.cc/virtual/2024/poster/96883,,,https://openreview.net/forum?id=18FGRNd0wZ,/media/PosterPDFs/NeurIPS%202024/96883.png?t=1733428872.6393995
10,93,-0.18803668,0.09546091,4,-0.20931696028541216,-0.0035235230900599545,"[0.012589192967312852, 1.289216406522538e-14, 0.003389177907990273, 5.0395594201895784e-06, 0.9840165895652637]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,18RdkSv9h9,FINALLY: fast and universal speech enhancement with studio-like quality,speech enhancement; generative models,6.5,4.75,Nicholas Babaev;Kirill Tamogashev;Azat Saginbaev;Ivan Shchekotov;Hanbin Bae;Hosang Sung;WonJun Lee;Hoon-Young Cho;Pavel Andreev,"Samsung;Skolkovo Institute of Science and Technology;Moscow Institute of Physics and Technology;Samsung;Samsung;Samsung;Higher School of Economics, Higher School of Economics",Researcher;MS student;MS student;Principal Researcher;Researcher;Vice President;MS student,https://neurips.cc/virtual/2024/poster/96882,,,https://openreview.net/forum?id=18RdkSv9h9,/media/PosterPDFs/NeurIPS%202024/96882.png?t=1731683595.700073
10,94,0.32727078,-0.11709024,1,0.4075643889177964,-0.08207163922598883,"[0.00461780523144997, 0.9939198756385793, 3.003487787416796e-20, 0.0014623191297679315, 2.0271049077615002e-13]","[0.015368121786900524, 0.012138964543215669]",0.18329293080760967,1ATLLgvURu,Learning-Augmented Priority Queues,learning-augmented algorithms;algorithms with predictions;priority queue;shortest paths;Dijkstra,5.75,4.25,Ziyad Benomar;Christian Coester,University of Oxford,Associate Professor,https://neurips.cc/virtual/2024/poster/96881,,,https://openreview.net/forum?id=1ATLLgvURu,
10,95,0.3095995,0.5030761,2,-0.09463330063911646,0.3327342704201369,"[0.043496203321004935, 5.146041552313105e-12, 0.9565037966736466, 4.015007435299887e-14, 1.6250988643882137e-13]","[0.018492172044200277, 0.005398682459816935]",0.18784501012503751,1BZKqZphsW,Risk-Averse Fine-tuning of Large Language Models,Risk Averse Reinforcement Learning;Large Language Model Finetuning,5.8,3.2,Sapana Chaudhary;Ujwal Dinesha;Dileep Kalathil;Srinivas Shakkottai,Texas A&M University;Texas A&M University - College Station;Texas A&M University;Texas A&M,PhD student;PhD student;Associate Professor;Full Professor,https://neurips.cc/virtual/2024/poster/96880,,,https://openreview.net/forum?id=1BZKqZphsW,/media/PosterPDFs/NeurIPS%202024/96880.png?t=1733328781.5713553
10,96,-0.26364937,-0.38828564,3,-0.12517292191148427,-0.27255963411007533,"[0.005308275999614651, 6.049159894189042e-07, 1.9158998982837986e-25, 0.9946512411398929, 3.987794450296695e-05]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,1CssOqRYyz,Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds,compression;point cloud;diffusion,4.0,4.0,Kai Liu;Kang You;Pan Gao,"Nanjing University of Aeronautics and Astronautics;Nanjing university;Nanjing University of Aeronautics and Astronautics, Tsinghua University",MS student;PhD student;Associate Professor,,,,,
10,97,-0.25224024,-0.31188005,3,-0.12517292191148427,-0.27255963411007533,"[0.014108669604485136, 1.8550672646197638e-07, 1.8020840039979107e-20, 0.9840860582800969, 0.001805086608691609]","[0.015175724772928962, 0.008565803978453268]",0.18025906515152407,1Du3mMP5YN,Learning to Shape In-distribution Feature Space for Out-of-distribution Detection,Out-of-distribution Detection,5.75,4.0,Yonggang Zhang;Jie Lu;Bo Peng;Zhen Fang;Yiu-ming Cheung,Hong Kong Baptist University;University of Technology Sydney;University of Technology Sydney,Postdoc;Professor;Assistant Professor,https://neurips.cc/virtual/2024/poster/96879,,,https://openreview.net/forum?id=1Du3mMP5YN,/media/PosterPDFs/NeurIPS%202024/96879.png?t=1731745181.7993424
10,98,-0.30068702,-0.14781809,4,-0.20931696028541216,-0.0035235230900599545,"[0.019567835130784025, 2.8997378249599496e-11, 1.7806330549867332e-10, 0.060827643084142395, 0.919604521578013]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,1ELFGSNBGC,Multiview Scene Graph,scene representation; spatial understanding; place recognition; object correspondence; scene graph,5.25,3.25,Juexiao Zhang;Gao Zhu;Sihang Li;Xinhao Liu;Haorui Song;Xinran Tang;Chen Feng,New York University;New York University;New York University;New York University;New York University;New York University;New York University,PhD student;MS student;PhD student;PhD student;MS student;MS student;Assistant Professor,https://neurips.cc/virtual/2024/poster/96878,,,https://openreview.net/forum?id=1ELFGSNBGC,/media/PosterPDFs/NeurIPS%202024/96878.png?t=1731728482.5838113
10,99,-0.09486352,0.005280091,4,-0.20931696028541216,-0.0035235230900599545,"[0.29901435797665843, 5.990543370798956e-09, 1.694117001606617e-06, 0.0038631427641526626, 0.6971207991516439]","[0.005801786813479695, 0.006326694821226842]",0.23054429689964853,1F32iCJFfa,Schrodinger Bridge Flow for Unpaired Data Translation,unpaired data translation;diffusion models;Schrodinger bridge;bridge matching;stochastic interpolant;flow matching,6.5,4.0,Valentin De Bortoli;Iryna Korshunova;Andriy Mnih;Arnaud Doucet,University of Oxford;Google DeepMind;Google DeepMind;University of Oxford,Postdoc;Researcher;Research Scientist;Full Professor,https://neurips.cc/virtual/2024/poster/96877,,,https://openreview.net/forum?id=1F32iCJFfa,/media/PosterPDFs/NeurIPS%202024/96877.png?t=1731688420.732189