Geometry-aware instance-reweighted adversarial training J Zhang, J Zhu, G Niu, B Han, M Sugiyama, M Kankanhalli arXiv preprint arXiv:2010.01736, 2020 | 249 | 2020 |
Reliable adversarial distillation with unreliable teachers J Zhu, J Yao, B Han, J Zhang, T Liu, G Niu, J Zhou, J Xu, H Yang arXiv preprint arXiv:2106.04928, 2021 | 53 | 2021 |
DeepInception: Hypnotize Large Language Model to Be Jailbreaker X Li, Z Zhou, J Zhu, J Yao, T Liu, B Han arXiv preprint arXiv:2311.03191, 2023 | 23 | 2023 |
Understanding the interaction of adversarial training with noisy labels J Zhu, J Zhang, B Han, T Liu, G Niu, H Yang, M Kankanhalli, M Sugiyama arXiv preprint arXiv:2102.03482, 2021 | 23 | 2021 |
Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability J Zhu, H Li, J Yao, T Liu, J Xu, B Han arXiv preprint arXiv:2306.03715, 2023 | 5 | 2023 |
Combating Exacerbated Heterogeneity for Robust Models in Federated Learning J Zhu, J Yao, T Liu, Q Yao, J Xu, B Han arXiv preprint arXiv:2303.00250, 2023 | 4 | 2023 |
Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks J Zhou, J Zhu, J Zhang, T Liu, G Niu, B Han, M Sugiyama Advances in Neural Information Processing Systems 35, 23621-23633, 2022 | 4 | 2022 |
Diversified outlier exposure for out-of-distribution detection via informative extrapolation J Zhu, Y Geng, J Yao, T Liu, G Niu, M Sugiyama, B Han Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
Exploring model dynamics for accumulative poisoning discovery J Zhu, X Guo, J Yao, C Du, L He, S Yuan, T Liu, L Wang, B Han International Conference on Machine Learning, 42983-43004, 2023 | | 2023 |