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You could try TRADES, which is a commonly used loss function aimed at reducing the trade-off between robustness and accuracy (using clean and adversarial images), and compare the performance. Training on clean examples during training can sometimes reduce the final model's PGD test accuracy.
Hi, Does anyone can help me to understand why not using clean samples during training? Will it reduce the performance? Thanks~
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