A large benchmark of 16 backdoor mitigation methods shows high performance variability across settings, with only FT-SAM and SAU outperforming their baselines, and most newer methods failing to beat FP and FT.
Backdoor learning: A survey,
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Countering Backdoor Attacks in Image Recognition: A Survey and Evaluation of Mitigation Strategies
A large benchmark of 16 backdoor mitigation methods shows high performance variability across settings, with only FT-SAM and SAU outperforming their baselines, and most newer methods failing to beat FP and FT.