2 papers
cs.CL2025
PARA: Parameter-Efficient Fine-tuning with Prompt Aware Representation Adjustment
Zequan Liu, Yi Zhao, Ming Tan +2
In the realm of parameter-efficient fine-tuning (PEFT) methods, while options like LoRA are available, there is a persistent demand in the industry for a PEFT approach that excels…
cs.CL2024
ALoRA: Allocating Low-Rank Adaptation for Fine-tuning Large Language Models
Zequan Liu, Jiawen Lyn, Wei Zhu +2
Parameter-efficient fine-tuning (PEFT) is widely studied for its effectiveness and efficiency in the era of large language models. Low-rank adaptation (LoRA) has demonstrated comme…