The BatchNorm Illusion: Diagnosing Normalization Artifacts in Machine Unlearning Evaluation
A previously undocumented confound in how unlearning is evaluated on BatchNorm-based architectures is identified: a single forward pass over retain data, an operation that modifies no weight, can deterministically rewrite the model's normalization state and reverse the apparent surface-metric forgetting.
Aaryaman Kalani, Murari Mandal, Dhruv Kumar et al.
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