AIBullisharXiv – CS AI · 6h ago7/10
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Rethinking Adapter Placement: A Dominant Adaptation Module Perspective
Researchers introduce DomLoRA, a parameter-efficient fine-tuning method that identifies a single 'dominant adaptation module' where most gradient energy concentrates, achieving superior performance with only 0.7% of standard LoRA's trainable parameters. The discovery reveals that optimal adapter placement is architecture-dependent but task-stable across instruction following, reasoning, and code generation applications.