rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking Paper • 2501.04519 • Published Jan 8 • 276
FAST: Efficient Action Tokenization for Vision-Language-Action Models Paper • 2501.09747 • Published Jan 16 • 24
Test-Time Preference Optimization: On-the-Fly Alignment via Iterative Textual Feedback Paper • 2501.12895 • Published Jan 22 • 61
Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models Paper • 2501.13629 • Published Jan 23 • 48
Can We Generate Images with CoT? Let's Verify and Reinforce Image Generation Step by Step Paper • 2501.13926 • Published Jan 23 • 42
ScoreFlow: Mastering LLM Agent Workflows via Score-based Preference Optimization Paper • 2502.04306 • Published Feb 6 • 19
ChartCitor: Multi-Agent Framework for Fine-Grained Chart Visual Attribution Paper • 2502.00989 • Published Feb 3 • 8
PILAF: Optimal Human Preference Sampling for Reward Modeling Paper • 2502.04270 • Published Feb 6 • 11
Show-o Turbo: Towards Accelerated Unified Multimodal Understanding and Generation Paper • 2502.05415 • Published Feb 8 • 22
MM-RLHF: The Next Step Forward in Multimodal LLM Alignment Paper • 2502.10391 • Published Feb 14 • 35
ImageRAG: Dynamic Image Retrieval for Reference-Guided Image Generation Paper • 2502.09411 • Published Feb 13 • 20
AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence Paper • 2502.13943 • Published Feb 19 • 8
MLGym: A New Framework and Benchmark for Advancing AI Research Agents Paper • 2502.14499 • Published Feb 20 • 192
SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features Paper • 2502.14786 • Published Feb 20 • 144
How Much Knowledge Can You Pack into a LoRA Adapter without Harming LLM? Paper • 2502.14502 • Published Feb 20 • 91
SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines Paper • 2502.14739 • Published Feb 20 • 103
Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning Paper • 2502.14768 • Published Feb 20 • 48
Discovering highly efficient low-weight quantum error-correcting codes with reinforcement learning Paper • 2502.14372 • Published Feb 20 • 36
S^2R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning Paper • 2502.12853 • Published Feb 18 • 29
Multimodal Inconsistency Reasoning (MMIR): A New Benchmark for Multimodal Reasoning Models Paper • 2502.16033 • Published Feb 22 • 18
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution Paper • 2502.18449 • Published Feb 25 • 74