Jinwoo Kim

FiLoRA: Focus-and-Ignore LoRA for Controllable Feature Reliance

FiLoRA is introduced, an instruction-conditioned, parameter-efficient adaptation framework that enables controllable modulation of feature reliance while keeping the task and predictive objective fixed and suggests that instruction-conditioned parameter adaptation can serve as a practical mechanism for intervening on internal model behavior.