parameter-efficient fine-tuning

Parameter-Efficient Fine-Tuning (PEFT) is a technique used to adapt pre-trained models to new tasks with minimal changes to the model's parameters. This approach is particularly useful in scenarios where computational resources are limited or when it is desirable to maintain the original model's performance on the initial task.

Papers

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Showing 701–710 of 935 papers

Title	Date	Tasks	Status	Hype
LoRA-drop: Efficient LoRA Parameter Pruning based on Output Evaluation	Feb 12, 2024	parameter-efficient fine-tuning	—Unverified	0
Learning to Route Among Specialized Experts for Zero-Shot Generalization	Feb 8, 2024	parameter-efficient fine-tuningZero-shot Generalization	CodeCode Available	2
L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models	Feb 7, 2024	Few-Shot LearningIn-Context Learning	—Unverified	0
Open-Vocabulary Calibration for Fine-tuned CLIP	Feb 7, 2024	parameter-efficient fine-tuningPrompt Learning	CodeCode Available	1
Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning	Feb 6, 2024	parameter-efficient fine-tuningRetrieval	CodeCode Available	1
Low-rank Attention Side-Tuning for Parameter-Efficient Fine-Tuning	Feb 6, 2024	GPUparameter-efficient fine-tuning	—Unverified	0
Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning	Feb 4, 2024	Image RetrievalMetric Learning	CodeCode Available	0
Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models	Feb 4, 2024	parameter-efficient fine-tuning	CodeCode Available	1
Enhancing the efficiency of protein language models with minimal wet-lab data through few-shot learning	Feb 3, 2024	Few-Shot LearningLearning-To-Rank	—Unverified	0
Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey	Feb 3, 2024	parameter-efficient fine-tuningTransfer Learning	CodeCode Available	4

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All datasets BoolQ HellaSwag WinoGrande

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	LLaMA2-7b	Accuracy (% )	82.63	—	Unverified
2	LLaMA2-7b	Accuracy (% )	82.63	—	Unverified
3	LLaMA2-7b	Accuracy (% )	81.93	—	Unverified
4	LLaMA2-7b	Accuracy (% )	80.28	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LLaMA2-7b	Accuracy (% )	76.68	—	Unverified
2	LLaMA2-7b	Accuracy (% )	76.67	—	Unverified
3	LLaMA2-7b	Accuracy (% )	76.27	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LLaMA2-7b	Accuracy (% )	70.8	—	Unverified
2	LLaMA2-7b	Accuracy (% )	70.09	—	Unverified
3	LLaMA2-7b	Accuracy (% )	69.85	—	Unverified