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Quantization Reading-List

about 17 hours ago

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Paper • 2208.07339 • Published Aug 15, 2022 • 5
GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Paper • 2210.17323 • Published Oct 31, 2022 • 8
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

Paper • 2211.10438 • Published Nov 18, 2022 • 6
QLoRA: Efficient Finetuning of Quantized LLMs

Paper • 2305.14314 • Published May 23, 2023 • 55

A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings

Paper • 2504.15610 • Published Apr 22 • 1
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models

Paper • 2502.13533 • Published Feb 19 • 11
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models

Paper • 2403.08822 • Published Feb 28, 2024
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?

Paper • 2407.18242 • Published Jul 25, 2024

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 152
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17, 2024 • 32
Tuning Language Models by Proxy

Paper • 2401.08565 • Published Jan 16, 2024 • 24
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10, 2024 • 70

QuIP: 2-Bit Quantization of Large Language Models With Guarantees

Paper • 2307.13304 • Published Jul 25, 2023 • 2
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Paper • 2306.03078 • Published Jun 5, 2023 • 3
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Paper • 2308.13137 • Published Aug 25, 2023 • 18
AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Paper • 2306.00978 • Published Jun 1, 2023 • 10

LoRA ensembles for large language model fine-tuning

Paper • 2310.00035 • Published Sep 29, 2023 • 2
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 28
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 44
LoRA Learns Less and Forgets Less

Paper • 2405.09673 • Published May 15, 2024 • 89

llm-performance

QLoRA: Efficient Finetuning of Quantized LLMs

Paper • 2305.14314 • Published May 23, 2023 • 55
Training Transformers with 4-bit Integers

Paper • 2306.11987 • Published Jun 21, 2023 • 22
FasterViT: Fast Vision Transformers with Hierarchical Attention

Paper • 2306.06189 • Published Jun 9, 2023 • 30
DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models

Paper • 2309.14509 • Published Sep 25, 2023 • 20

XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference

Paper • 2404.15420 • Published Apr 23, 2024 • 11
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework

Paper • 2404.14619 • Published Apr 22, 2024 • 128
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Paper • 2404.14219 • Published Apr 22, 2024 • 257
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 46

DocGraphLM: Documental Graph Language Model for Information Extraction

Paper • 2401.02823 • Published Jan 5, 2024 • 37
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 44
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 28

Papers related to parameter efficient finetuning methods.

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 28
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 44

LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 28
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 44
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
LoRA ensembles for large language model fine-tuning

Paper • 2310.00035 • Published Sep 29, 2023 • 2

Quantization Reading-List

about 17 hours ago

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Paper • 2208.07339 • Published Aug 15, 2022 • 5
GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Paper • 2210.17323 • Published Oct 31, 2022 • 8
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

Paper • 2211.10438 • Published Nov 18, 2022 • 6
QLoRA: Efficient Finetuning of Quantized LLMs

Paper • 2305.14314 • Published May 23, 2023 • 55

llm-performance

QLoRA: Efficient Finetuning of Quantized LLMs

Paper • 2305.14314 • Published May 23, 2023 • 55
Training Transformers with 4-bit Integers

Paper • 2306.11987 • Published Jun 21, 2023 • 22
FasterViT: Fast Vision Transformers with Hierarchical Attention

Paper • 2306.06189 • Published Jun 9, 2023 • 30
DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models

Paper • 2309.14509 • Published Sep 25, 2023 • 20

A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings

Paper • 2504.15610 • Published Apr 22 • 1
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models

Paper • 2502.13533 • Published Feb 19 • 11
LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models

Paper • 2403.08822 • Published Feb 28, 2024
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?

Paper • 2407.18242 • Published Jul 25, 2024

XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference

Paper • 2404.15420 • Published Apr 23, 2024 • 11
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework

Paper • 2404.14619 • Published Apr 22, 2024 • 128
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Paper • 2404.14219 • Published Apr 22, 2024 • 257
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22, 2024 • 46

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 152
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17, 2024 • 32
Tuning Language Models by Proxy

Paper • 2401.08565 • Published Jan 16, 2024 • 24
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10, 2024 • 70

DocGraphLM: Documental Graph Language Model for Information Extraction

Paper • 2401.02823 • Published Jan 5, 2024 • 37
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 44
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 28

QuIP: 2-Bit Quantization of Large Language Models With Guarantees

Paper • 2307.13304 • Published Jul 25, 2023 • 2
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Paper • 2306.03078 • Published Jun 5, 2023 • 3
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Paper • 2308.13137 • Published Aug 25, 2023 • 18
AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Paper • 2306.00978 • Published Jun 1, 2023 • 10

Papers related to parameter efficient finetuning methods.

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 28
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 44

LoRA ensembles for large language model fine-tuning

Paper • 2310.00035 • Published Sep 29, 2023 • 2
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 28
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 44
LoRA Learns Less and Forgets Less

Paper • 2405.09673 • Published May 15, 2024 • 89

LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Paper • 2310.08659 • Published Oct 12, 2023 • 28
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 44
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1
LoRA ensembles for large language model fine-tuning

Paper • 2310.00035 • Published Sep 29, 2023 • 2

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