How Hard Can It Be? Hardness-Aware Multi-Objective Unlearning 事件

How Hard Can It Be? Hardness-Aware Multi-Objective Unlearning arXiv:2606.02119v1 Announce Type: cross Abstract: Machine unlearning aims to remove the influence of specific forget training data due to privacy, copyright or bias concerns while maintaining the model performance on the remaining retain data. Existing unlearning algorithms, such as optimizing a weighted combination of losses, have tried to achieve these objectives of improving forget quality and maintaining retain utility. However,