Guided Input Calibration aligns any auxiliary dataset with a victim model's learned features before backdoor purification, consistently improving clean accuracy across dataset types with variable effects on attack success rate.
A new backdoor attack in cnns by training set corruption without label poisoning
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Revisiting the Auxiliary Data in Backdoor Purification
Guided Input Calibration aligns any auxiliary dataset with a victim model's learned features before backdoor purification, consistently improving clean accuracy across dataset types with variable effects on attack success rate.