Xilie Xu

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 17

Top Topics

Diffusion Models

Decision Boundary

Top Venues

Publications

Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang
Privacy-Preserving Low-Rank Adaptation for Latent Diffusion Models. CoRR (2024)
Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli
An LLM can Fool Itself: A Prompt-Based Adversarial Attack. ICLR (2024)
Xilie Xu, Jingfeng Zhang, Mohan S. Kankanhalli
AutoLoRa: An Automated Robust Fine-Tuning Framework. ICLR (2024)
Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli
An LLM can Fool Itself: A Prompt-Based Adversarial Attack. CoRR (2023)
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection. CoRR (2023)
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection. NeurIPS (2023)
Chen Chen, Jingfeng Zhang, Xilie Xu, Lingjuan Lyu, Chaochao Chen, Tianlei Hu, Gang Chen
Decision Boundary-Aware Data Augmentation for Adversarial Training. IEEE Trans. Dependable Secur. Comput. 20 (3) (2023)
Xilie Xu, Jingfeng Zhang, Mohan S. Kankanhalli
AutoLoRa: A Parameter-Free Automated Robust Fine-Tuning Framework. CoRR (2023)
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization. CoRR (2023)
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization. NeurIPS (2023)
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
Adversarial Attack and Defense for Non-Parametric Two-Sample Tests. ICML (2022)
Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Lizhen Cui, Gang Niu, Masashi Sugiyama
NoiLin: Improving adversarial training and correcting stereotype of noisy labels. Trans. Mach. Learn. Res. 2022 (2022)
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
Adversarial Attacks and Defense for Non-Parametric Two-Sample Tests. CoRR (2022)
Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Gang Niu, Lizhen Cui, Masashi Sugiyama
NoiLIn: Do Noisy Labels Always Hurt Adversarial Training? CoRR (2021)
Chen Chen, Jingfeng Zhang, Xilie Xu, Tianlei Hu, Gang Niu, Gang Chen, Masashi Sugiyama
Guided Interpolation for Adversarial Training. CoRR (2021)
Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan S. Kankanhalli
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger. CoRR (2020)
Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan S. Kankanhalli
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger. ICML (2020)