Adapter-Augmented Dual-Stream Update for Persistent Knowledge Erasure
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Lethe: Adapter-Augmented Dual-Stream Update for Persistent Knowledge Erasure in Federated Unlearning
Announce Type: replace Abstract: Federated unlearning (FU) aims to erase designated client-level, class-level, or sample-level knowledge from a global model. Existing studies commonly assume that the collaboration ends with the unlearning operation, overlooking the follow-up situation where federated training continues over the remaining data. We identify a critical failure mode, termed knowledge resurfacing, by revealing that continued training can re-activate unlearned knowledge and cause...