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Found 2 papers, 2 papers with code
Annealing Self-Distillation Rectification Improves Adversarial Training
To address this issue and enhance adversarial robustness, we analyze the characteristics of robust models and identify that robust models tend to produce smoother and well-calibrated outputs.
Enhancing Targeted Attack Transferability via Diversified Weight Pruning
In this work, we propose Diversified Weight Pruning (DWP), a novel model augmentation technique for generating transferable targeted attacks.
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