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Collections including paper arxiv:2305.18403

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

Paper • 2504.15610 • Published Apr 22, 2025 • 1
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models

Paper • 2502.13533 • Published Feb 19, 2025 • 13
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

Papers: Quantization

FP8-LM: Training FP8 Large Language Models

Paper • 2310.18313 • Published Oct 27, 2023 • 33
LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Paper • 2310.16836 • Published Oct 25, 2023 • 14
TEQ: Trainable Equivalent Transformation for Quantization of LLMs

Paper • 2310.10944 • Published Oct 17, 2023 • 10
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1

Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time

Paper • 2310.17157 • Published Oct 26, 2023 • 14
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers

Paper • 2305.15805 • Published May 25, 2023 • 1
Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt

Paper • 2305.11186 • Published May 17, 2023 • 1
Composable Sparse Fine-Tuning for Cross-Lingual Transfer

Paper • 2110.07560 • Published Oct 14, 2021 • 2

Papers: Pruning

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LoRAPrune: Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Paper • 2305.18403 • Published May 28, 2023 • 2
Parameter-Efficient Fine-Tuning with Layer Pruning on Free-Text Sequence-to-Sequence Modeling

Paper • 2305.08285 • Published May 15, 2023 • 1
A Comparative Analysis of Task-Agnostic Distillation Methods for Compressing Transformer Language Models

Paper • 2310.08797 • Published Oct 13, 2023 • 1

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 • 27
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 • 45

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

Paper • 2310.08659 • Published Oct 12, 2023 • 27
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 45
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

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

Paper • 2504.15610 • Published Apr 22, 2025 • 1
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models

Paper • 2502.13533 • Published Feb 19, 2025 • 13
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

Papers: Pruning

LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery

Paper • 2310.18356 • Published Oct 24, 2023 • 24
LoRAPrune: Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Paper • 2305.18403 • Published May 28, 2023 • 2
Parameter-Efficient Fine-Tuning with Layer Pruning on Free-Text Sequence-to-Sequence Modeling

Paper • 2305.08285 • Published May 15, 2023 • 1
A Comparative Analysis of Task-Agnostic Distillation Methods for Compressing Transformer Language Models

Paper • 2310.08797 • Published Oct 13, 2023 • 1

Papers: Quantization

FP8-LM: Training FP8 Large Language Models

Paper • 2310.18313 • Published Oct 27, 2023 • 33
LLM-FP4: 4-Bit Floating-Point Quantized Transformers

Paper • 2310.16836 • Published Oct 25, 2023 • 14
TEQ: Trainable Equivalent Transformation for Quantization of LLMs

Paper • 2310.10944 • Published Oct 17, 2023 • 10
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

Paper • 2309.16119 • Published Sep 28, 2023 • 1

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 • 27
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 • 45

Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time

Paper • 2310.17157 • Published Oct 26, 2023 • 14
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers

Paper • 2305.15805 • Published May 25, 2023 • 1
Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt

Paper • 2305.11186 • Published May 17, 2023 • 1
Composable Sparse Fine-Tuning for Cross-Lingual Transfer

Paper • 2110.07560 • Published Oct 14, 2021 • 2

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

Paper • 2310.08659 • Published Oct 12, 2023 • 27
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Paper • 2309.14717 • Published Sep 26, 2023 • 45
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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