Confess What You Know: Forget-Set Misalignment with Model Knowledge in LLM Unlearning
CONfession-to-Forget-Set (CONFS), a data-blind framework that constructs model-aligned forget sets by eliciting and formalizing the model's memorized knowledge, approaches Gold-standard performance on several metrics and achieves a competitive forgetting-utility balance, while preserving utility better than other data-...
Miso Kim, Georu Lee, Seungwon Jeong et al.
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