ECCV Paper: Locality-Aware Continual Unlearning for Diffusion Models
mittu1204 · x · 2026-08-31
To address the need for continual concept removal in deployed diffusion models (privacy, copyright, safety), this paper proposes Locality-Aware Continual Unlearning (LACU). Existing methods collapse after 3-5 sequential uses due to coarse targets and lack of protection for neighboring concepts. LACU introduces Locality-Aware Target Selection (picking semantically closest retain prompts) and Locality-Aware Replay (replaying nearest neighbors) to mitigate degradation, enabling stable continual unlearning.
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