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Apr 5, 2024
Apr 5, 2024Collections
Discover the best community collections!
Collections including paper arxiv:2402.11295
Collection by
Mar 16, 2024
Mar 16, 2024-
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 628 -
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 • 50
Collection by
4 days ago
4 days ago-
LoRA+: Efficient Low Rank Adaptation of Large Models
Paper • 2402.12354 • Published • 7 -
The FinBen: An Holistic Financial Benchmark for Large Language Models
Paper • 2402.12659 • Published • 23 -
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Paper • 2402.13249 • Published • 14 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 69
Collection by
May 1, 2024
May 1, 2024-
BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 22 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 24 -
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 50 -
GPTVQ: The Blessing of Dimensionality for LLM Quantization
Paper • 2402.15319 • Published • 22
Collection by
Nov 10, 2024
Nov 10, 2024-
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 50 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 24 -
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
Collection by
Aug 5
Aug 5-
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 628 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 24 -
EasyInstruct: An Easy-to-use Instruction Processing Framework for Large Language Models
Paper • 2402.03049 • Published • 1 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 263
Collection by
Mar 12, 2024
Mar 12, 2024Collection by
Feb 23, 2024
Feb 23, 2024-
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Paper • 2402.13249 • Published • 14 -
The FinBen: An Holistic Financial Benchmark for Large Language Models
Paper • 2402.12659 • Published • 23 -
Instruction-tuned Language Models are Better Knowledge Learners
Paper • 2402.12847 • Published • 26 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50
Collection by
Feb 28, 2024
Feb 28, 2024-
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 50 -
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
Paper • 2401.18079 • Published • 8 -
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 • 24
Collection by
Mar 18, 2024
Mar 18, 2024-
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Paper • 2401.15024 • Published • 74 -
FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design
Paper • 2401.14112 • Published • 20 -
WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models
Paper • 2401.13919 • Published • 32 -
Sketch2NeRF: Multi-view Sketch-guided Text-to-3D Generation
Paper • 2401.14257 • Published • 12
Collection by
Apr 5, 2024
Apr 5, 2024Collection by
Aug 5
Aug 5-
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 628 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 24 -
EasyInstruct: An Easy-to-use Instruction Processing Framework for Large Language Models
Paper • 2402.03049 • Published • 1 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 263
Collection by
Mar 16, 2024
Mar 16, 2024-
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 628 -
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 • 50
Collection by
Mar 12, 2024
Mar 12, 2024Collection by
4 days ago
4 days ago-
LoRA+: Efficient Low Rank Adaptation of Large Models
Paper • 2402.12354 • Published • 7 -
The FinBen: An Holistic Financial Benchmark for Large Language Models
Paper • 2402.12659 • Published • 23 -
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Paper • 2402.13249 • Published • 14 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 69
Collection by
Feb 23, 2024
Feb 23, 2024-
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Paper • 2402.13249 • Published • 14 -
The FinBen: An Holistic Financial Benchmark for Large Language Models
Paper • 2402.12659 • Published • 23 -
Instruction-tuned Language Models are Better Knowledge Learners
Paper • 2402.12847 • Published • 26 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 50
Collection by
May 1, 2024
May 1, 2024-
BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 22 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 24 -
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 50 -
GPTVQ: The Blessing of Dimensionality for LLM Quantization
Paper • 2402.15319 • Published • 22
Collection by
Feb 28, 2024
Feb 28, 2024-
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 50 -
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
Paper • 2401.18079 • Published • 8 -
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 • 24
Collection by
Nov 10, 2024
Nov 10, 2024-
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 50 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 24 -
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
Collection by
Mar 18, 2024
Mar 18, 2024-
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Paper • 2401.15024 • Published • 74 -
FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design
Paper • 2401.14112 • Published • 20 -
WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models
Paper • 2401.13919 • Published • 32 -
Sketch2NeRF: Multi-view Sketch-guided Text-to-3D Generation
Paper • 2401.14257 • Published • 12