Class Unlearning via Depth-Aware Removal of Forget-Specific Directions

Researchers introduce DAMP, a weight-surgery technique for machine unlearning that removes forget-class information from deep model layers rather than just suppressing classifier outputs. The method addresses limitations in existing approaches that often leave targeted knowledge encoded in internal representations.

MentionsDAMP · machine unlearning

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