LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery Paper • 2310.18356 • Published Oct 24, 2023 • 22
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models Paper • 2310.08659 • Published Oct 12, 2023 • 22
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
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models Paper • 2309.12307 • Published Sep 21, 2023 • 87
LoRA-FA: Memory-efficient Low-rank Adaptation for Large Language Models Fine-tuning Paper • 2308.03303 • Published Aug 7, 2023 • 3
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
Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning Paper • 2303.15647 • Published Mar 28, 2023 • 4
Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning Paper • 2205.05638 • Published May 11, 2022 • 3
DEFT: Data Efficient Fine-Tuning for Large Language Models via Unsupervised Core-Set Selection Paper • 2310.16776 • Published Oct 25, 2023
S-LoRA: Serving Thousands of Concurrent LoRA Adapters Paper • 2311.03285 • Published Nov 6, 2023 • 28
A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA Paper • 2312.03732 • Published Nov 28, 2023 • 7
MoELoRA: Contrastive Learning Guided Mixture of Experts on Parameter-Efficient Fine-Tuning for Large Language Models Paper • 2402.12851 • Published Feb 20 • 2