arXiv cs.CL
· Papers
Attention-Guided Layer Selection for Contrastive Decoding in Large Language Models
arXiv:2607.23067v1 Announce Type: new Abstract: Contrastive decoding methods such as DoLa improve the factuality of Large Language Models (LLMs) by contrasting the output distributions of mature and premature layers. However, DoLa's dynamic layer selection relies solely on divergences in output vocabulary distributions