Channel-Level Semantic Perturbations: Unlearnable Examples for Diverse Training Paradigms
概要
arXiv:2605.05224v1 Announce Type: cross Abstract: The unauthorized use of personal data in model training has emerged as a growing privacy threat. Unlearnable examples (UEs) address this issue by embedding imperceptible perturbations into benign examples to obstruct feature learning. However, exist…
