Xilie Xu

20 papers A* 8Journal 12
YearRankTypeTitle / Venue / Authors
2025 A* conf
Privacy-Preserving Low-Rank Adaptation Against Membership Inference Attacks for Latent Diffusion Models.
AAAI
Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang
2024 A* conf
An LLM can Fool Itself: A Prompt-Based Adversarial Attack.
ICLR
Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli
2024 A* conf
AutoLoRa: An Automated Robust Fine-Tuning Framework.
ICLR
Xilie Xu, Jingfeng Zhang, Mohan S. Kankanhalli
2024 A* conf
Perplexity-aware Correction for Robust Alignment with Noisy Preferences.
NeurIPS
Keyi Kong, Xilie Xu, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli
2024 J jnl
Privacy-Preserving Low-Rank Adaptation for Latent Diffusion Models.
CoRR
Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang
2024 J jnl
Technical Report for ICML 2024 TiFA Workshop MLLM Attack Challenge: Suffix Injection and Projected Gradient Descent Can Easily Fool An MLLM.
CoRR
Yangyang Guo, Ziwei Xu, Xilie Xu, Yongkang Wong, Liqiang Nie, Mohan S. Kankanhalli
2023 J jnl
An LLM can Fool Itself: A Prompt-Based Adversarial Attack.
CoRR
Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli
2023 J jnl
AutoLoRa: A Parameter-Free Automated Robust Fine-Tuning Framework.
CoRR
Xilie Xu, Jingfeng Zhang, Mohan S. Kankanhalli
2023 J jnl
Decision Boundary-Aware Data Augmentation for Adversarial Training.
IEEE Trans. Dependable Secur. Comput.
Chen Chen, Jingfeng Zhang, Xilie Xu, Lingjuan Lyu, Chaochao Chen, Tianlei Hu, Gang Chen
2023 A* conf
Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection.
NeurIPS
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
2023 J jnl
Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection.
CoRR
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
2023 A* conf
Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization.
NeurIPS
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
2023 J jnl
Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization.
CoRR
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
2022 A* conf
Adversarial Attack and Defense for Non-Parametric Two-Sample Tests.
ICML
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
2022 J jnl
Adversarial Attacks and Defense for Non-Parametric Two-Sample Tests.
CoRR
Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli
2022 J jnl
NoiLin: Improving adversarial training and correcting stereotype of noisy labels.
Trans. Mach. Learn. Res.
Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Lizhen Cui, Gang Niu, Masashi Sugiyama
2021 J jnl
Guided Interpolation for Adversarial Training.
CoRR
Chen Chen, Jingfeng Zhang, Xilie Xu, Tianlei Hu, Gang Niu, Gang Chen, Masashi Sugiyama
2021 J jnl
NoiLIn: Do Noisy Labels Always Hurt Adversarial Training?
CoRR
Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Gang Niu, Lizhen Cui, Masashi Sugiyama
2020 A* conf
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger.
ICML
Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan S. Kankanhalli
2020 J jnl
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger.
CoRR
Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan S. Kankanhalli