نسخة أولية وصول مفتوح
Dynamic Positional Attention Modulation for Parameter-Efficient Fine-Tuning of Large Language Models
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 …