A weight-permutation-based two-stage mode connectivity method purifies backdoored neural networks across supervised and self-supervised learning with few clean samples.
Architectural backdoors in neural networks
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Circumventing Backdoor Space via Weight Symmetry
A weight-permutation-based two-stage mode connectivity method purifies backdoored neural networks across supervised and self-supervised learning with few clean samples.