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Xinli Yue

2 accepted papers

2024

Revisiting Adversarial Training Under Long-Tailed Distributions

CVPR 2024poster

Deep neural networks are vulnerable to adversarial attacks leading to erroneous outputs. Adversarial training has been recognized as one of the most effective methods to counter such attacks. However existing adversarial training techniques have predominantly been evaluated on balanced datasets wher…

2023

Revisiting Adversarial Robustness Distillation from the Perspective of Robust Fairness

NeurIPS 2023poster

Adversarial Robustness Distillation (ARD) aims to transfer the robustness of large teacher models to small student models, facilitating the attainment of robust performance on resource-limited devices. However, existing research on ARD primarily focuses on the overall robustness of student models, o…