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cs.LG2026
Robust Continual Unlearning against Knowledge Erosion and Forgetting Reversal
Eun-Ju Park, Youjin Shin, Simon S. Woo
As a means to balance the growth of the AI industry with the need for privacy protection, machine unlearning plays a crucial role in realizing the ``right to be forgotten'' in arti…
cs.LG2026
Efficient Unlearning through Maximizing Relearning Convergence Delay
Khoa Tran, Simon S. Woo
Machine unlearning poses challenges in removing mislabeled, contaminated, or problematic data from a pretrained model. Current unlearning approaches and evaluation metrics are sole…
cs.CV2026
Suppression or Deletion: A Restoration-Based Representation-Level Analysis of Machine Unlearning
Yurim Jang, Jaeung Lee, Dohyun Kim +2
As pretrained models are increasingly shared on the web, ensuring that models can forget or delete sensitive, copyrighted, or private information upon request has become crucial. M…