On-the-go Forgetting without Explicit Unlearning via ERASE
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arXiv:2609.05966v1 Announce Type: cross Abstract: Existing unlearning approaches typically rely on post hoc weight adaptation or distillation, leading to duplicated memory costs, degraded generalization, and limited scalability. In this work, we introduce ERASE, Erasure via Reconstructive Adversari…
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- 2026-09-09 04:00 · arXiv stat.ML
On-the-go Forgetting without Explicit Unlearning via ERASE