RapidUn: Influence-Driven Parameter Reweighting for Efficient Large Language Model Unlearning
RapidUn, an influence-guided framework that converts cross-sample influence estimates into fixed sample-specific weights for weighted LoRA unlearning, is proposed, and complementary TOFU, semantic LLM-judge, and IFEval evaluations further support the effectiveness of influence-guided sample reweighting beyond the contr...