Xu, Xilie

9 publications

AAAI 2025 Privacy-Preserving Low-Rank Adaptation Against Membership Inference Attacks for Latent Diffusion Models Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang

ICLR 2024 An LLM Can Fool Itself: A Prompt-Based Adversarial Attack Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan Kankanhalli

ICLR 2024 AutoLoRa: An Automated Robust Fine-Tuning Framework Xilie Xu, Jingfeng Zhang, Mohan Kankanhalli

NeurIPS 2024 Perplexity-Aware Correction for Robust Alignment with Noisy Preferences Keyi Kong, Xilie Xu, Di Wang, Jingfeng Zhang, Mohan Kankanhalli

NeurIPS 2023 Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S Kankanhalli

NeurIPS 2023 Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S Kankanhalli

ICML 2022 Adversarial Attack and Defense for Non-Parametric Two-Sample Tests Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan Kankanhalli

TMLR 2022 NoiLin: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Lizhen Cui, Gang Niu, Masashi Sugiyama

ICML 2020 Attacks Which Do Not Kill Training Make Adversarial Learning Stronger Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan Kankanhalli