Parameter-efficient fine-tuning (PEFT) has become a standard approach for adapting large language models to downstream tasks. However, most existing PEFT methods rely on uniform and static adaptations, without accounting for the structured heterogeneity of attention across dimensions, heads, layers, and input tokens. I...
Dayan Pan, Jing-Yuan Wang, Xie Yu· Proceedings of the 32nd ACM...· 0 citations
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