When Priors Backfire: On the Vulnerability of Unlearnable Examples to Pretraining
arXiv:2603.04731v1 Announce Type: new Abstract: Unlearnable Examples (UEs) serve as a data protection strategy that generates imperceptible perturbations to mislead models into learning spurious correlations …
Zhihao Li, Gezheng Xu, Jiale Cai, Ruiyi Fang, Di Wu, Qicheng Lao, Charles Ling, Boyu Wang
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