Dong-Hai Zhu

Parameter-Efficient Fine-Tuning of Large Language Models via Deconvolution in Subspace

This paper proposes a novel parameter-efficient fine-tuning method that combines the knowledge completion capability of deconvolution with the subspace learning ability, reducing the number of parameters required for fine-tuning by 8 times . Experimental results demonstrate that our method achieves…