2 papers
cs.LG2026
Confusion-Geometry Rebalancing for Long-Tailed Adversarial Training
Mengnan Zhao, Geyong Min, Lihe Zhang +2
Adversarial training under long tailed distributions suffers from a dual imbalance: the class imbalance skews the training objective toward head classes, and the adversarial inner…
cs.LG2026
Mitigating Error Amplification in Fast Adversarial Training
Mengnan Zhao, Lihe Zhang, Bo Wang +3
Fast Adversarial Training (FAT) has proven effective in enhancing model robustness by encouraging networks to learn perturbation-invariant representations. However, FAT often suffe…