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Chain-of-Verification Reduces Hallucination in Large Language Models
Paper • 2309.11495 • Published • 39 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 78 -
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages
Paper • 2309.09400 • Published • 85 -
Language Modeling Is Compression
Paper • 2309.10668 • Published • 83
Collections
Discover the best community collections!
Collections including paper arxiv:2402.11295
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 615 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 25 -
EasyInstruct: An Easy-to-use Instruction Processing Framework for Large Language Models
Paper • 2402.03049 • Published • 1
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 615 -
Atom: Low-bit Quantization for Efficient and Accurate LLM Serving
Paper • 2310.19102 • Published • 11 -
AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning
Paper • 2311.00257 • Published • 10 -
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 51
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LoRA+: Efficient Low Rank Adaptation of Large Models
Paper • 2402.12354 • Published • 6 -
The FinBen: An Holistic Financial Benchmark for Large Language Models
Paper • 2402.12659 • Published • 22 -
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Paper • 2402.13249 • Published • 13 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 70
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TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Paper • 2402.13249 • Published • 13 -
The FinBen: An Holistic Financial Benchmark for Large Language Models
Paper • 2402.12659 • Published • 22 -
Instruction-tuned Language Models are Better Knowledge Learners
Paper • 2402.12847 • Published • 27 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 49
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BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 23 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 25 -
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 51 -
GPTVQ: The Blessing of Dimensionality for LLM Quantization
Paper • 2402.15319 • Published • 22
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BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 51 -
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
Paper • 2401.18079 • Published • 7 -
Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers
Paper • 2402.08958 • Published • 6 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 25
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BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 51 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 25 -
A Survey on Transformer Compression
Paper • 2402.05964 • Published • 1 -
Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers
Paper • 2402.08958 • Published • 6