作者位次 #3/6ACL 2026Poster· Natural Language Processing
L a C o: Layer-wise Compensation for Pruned Large Language Models
Yingen Liu · Fan Wu · Panxuyan · Ruihui Li · Zhuo Tang · Kenli Li
摘要
Pruning is essential for the efficient deployment of Large Language Models (LLMs); however, it causes severe performance degradation due to the structural distortion induced by sparsity.Existing recovery strategies, such as LoRA, predominantly employ global fine-tuning, often overlooking the mech...