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cs.LG2026
Mitigating Sequential Reappearance in Diffusion Data-Point Unlearning
Donghyun Kim, Taehyuk Lee, Jinyeong Kim +4
Diffusion data-point unlearning is typically evaluated immediately after each deletion, even though subsequent requests may repeatedly update the same model. We identify sequential…
cs.LG2026
Erase at the Core: Representation Unlearning for Machine Unlearning
Jaewon Lee, Yongwoo Kim, Donghyun Kim
Many approximate machine unlearning methods demonstrate strong logit-level forgetting -- such as near-zero accuracy on the forget set -- yet continue to preserve substantial inform…
cs.LG2025★ 3 cited
Are We Truly Forgetting? A Critical Re-examination of Machine Unlearning Evaluation Protocols
Yongwoo Kim, Sungmin Cha, Donghyun Kim
Machine unlearning is a process to remove specific data points from a trained model while maintaining the performance on the retain data, addressing privacy or legal requirements.…