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Collections including paper arxiv:2402.04291

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 48
OneBit: Towards Extremely Low-bit Large Language Models

Paper • 2402.11295 • Published Feb 17, 2024 • 23
A Survey on Transformer Compression

Paper • 2402.05964 • Published Feb 5, 2024
Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers

Paper • 2402.08958 • Published Feb 14, 2024 • 3

HensonResearchFor1BitLLMs

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 605
Atom: Low-bit Quantization for Efficient and Accurate LLM Serving

Paper • 2310.19102 • Published Oct 29, 2023 • 10
AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning

Paper • 2311.00257 • Published Nov 1, 2023 • 8
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 48

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 52
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Paper • 2403.03507 • Published Mar 6, 2024 • 183
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 48
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 605

BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15, 2024 • 19
OneBit: Towards Extremely Low-bit Large Language Models

Paper • 2402.11295 • Published Feb 17, 2024 • 23
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 48
GPTVQ: The Blessing of Dimensionality for LLM Quantization

Paper • 2402.15319 • Published Feb 23, 2024 • 19

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 104
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15, 2024 • 40
BitDelta: Your Fine-Tune May Only Be Worth One Bit

Paper • 2402.10193 • Published Feb 15, 2024 • 19
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Paper • 2402.09727 • Published Feb 15, 2024 • 36

Quantization techniques

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 48

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 48

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 48
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 605

Quantization | Compression

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 48
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization

Paper • 2401.18079 • Published Jan 31, 2024 • 7
Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers

Paper • 2402.08958 • Published Feb 14, 2024 • 3
OneBit: Towards Extremely Low-bit Large Language Models

Paper • 2402.11295 • Published Feb 17, 2024 • 23

20s LLM Toolbox

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 48
Self-Discover: Large Language Models Self-Compose Reasoning Structures

Paper • 2402.03620 • Published Feb 6, 2024 • 114
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks

Paper • 2402.04248 • Published Feb 6, 2024 • 30
Scaling Laws for Downstream Task Performance of Large Language Models

Paper • 2402.04177 • Published Feb 6, 2024 • 17

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