Adversarial Attacks and Defenses: Frontiers, Advances and Practice. - Han Xu 002; Yaxin Li 001; Wei Jin 009; Jiliang Tang (KDD, 2020)

Deep Adversarial Canonical Correlation Analysis. - Wenqi Fan; Yao Ma 001; Han Xu 002; Xiaorui Liu; Jianping Wang 001; Qing Li 001; Jiliang Tang (SDM, 2020)

Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study. - Wei Jin 009; Yaxin Li 001; Han Xu 002; Yiqi Wang 001; Jiliang Tang (CoRR, 2020)

DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses. - Yaxin Li 001; Wei Jin 009; Han Xu 002; Jiliang Tang (CoRR, 2020)

To be Robust or to be Fair: Towards Fairness in Adversarial Training. - Han Xu 002; Xiaorui Liu; Yaxin Li 001; Jiliang Tang (CoRR, 2020)

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review. - Han Xu 002; Yao Ma 001; Haochen Liu; Debayan Deb; Hui Liu 031; Jiliang Tang; Anil K. Jain 001 (Int. J. Autom. Comput., 2020)

Adversarial Attacks and Defenses on Graphs. - Wei Jin 009; Yaxin Li 001; Han Xu 002; Yiqi Wang 001; Shuiwang Ji; Charu Aggarwal 001; Jiliang Tang (SIGKDD Explor., 2020)

DeepRobust: a Platform for Adversarial Attacks and Defenses. - Yaxin Li 001; Wei Jin 009; Han Xu 002; Jiliang Tang (AAAI, 2021)

To be Robust or to be Fair: Towards Fairness in Adversarial Training. - Han Xu 002; Xiaorui Liu; Yaxin Li 001; Anil K. Jain 001; Jiliang Tang (ICML, 2021)

Adversarial Robustness in Deep Learning: From Practices to Theories. - Han Xu 002; Yaxin Li 001; Xiaorui Liu; Wentao Wang 006; Jiliang Tang (KDD, 2021)

Graph Neural Networks with Adaptive Residual. - Xiaorui Liu; Jiayuan Ding; Wei Jin 009; Han Xu 002; Yao Ma 001; Zitao Liu 001; Jiliang Tang (NeurIPS, 2021)

Yet Meta Learning Can Adapt Fast, it Can Also Break Easily. - Han Xu 002; Yaxin Li 001; Xiaorui Liu; Hui Liu 031; Jiliang Tang (SDM, 2021)

Towards the Memorization Effect of Neural Networks in Adversarial Training. - Han Xu 002; Xiaorui Liu; Wentao Wang 006; Wenbiao Ding; Zhongqin Wu; Zitao Liu 001; Anil K. Jain 001; Jiliang Tang (CoRR, 2021)

Imbalanced Adversarial Training with Reweighting. - Wentao Wang 006; Han Xu 002; Xiaorui Liu; Yaxin Li 001; Bhavani Thuraisingham; Jiliang Tang (ICDM, 2022)

Towards Adversarial Learning: From Evasion Attacks to Poisoning Attacks. - Wentao Wang 006; Han Xu 002; Yuxuan Wan; Jie Ren 019; Jiliang Tang (KDD, 2022)

Doctoral Consortium of WSDM'22: Exploring the Bias of Adversarial Defenses. - Han Xu 002 (WSDM, 2022)

Enhancing Adversarial Training with Feature Separability. - Yaxin Li 001; Xiaorui Liu; Han Xu 002; Wentao Wang 006; Jiliang Tang (CoRR, 2022)

Defense Against Gradient Leakage Attacks via Learning to Obscure Data. - Yuxuan Wan; Han Xu 002; Xiaorui Liu; Jie Ren 019; Wenqi Fan; Jiliang Tang (CoRR, 2022)

A Comprehensive Survey on Trustworthy Recommender Systems. - Wenqi Fan; Xiangyu Zhao 001; Xiao Chen 016; Jingran Su; Jingtong Gao; Lin Wang 040; Qidong Liu 002; Yiqi Wang 001; Han Xu 002; Lei Chen 002; Qing Li 001 (CoRR, 2022)

Probabilistic Categorical Adversarial Attack & Adversarial Training. - Pengfei He; Han Xu 002; Jie Ren 019; Yuxuan Wan; Zitao Liu 001; Jiliang Tang (CoRR, 2022)

Towards Fair Classification against Poisoning Attacks. - Han Xu 002; Xiaorui Liu; Yuxuan Wan; Jiliang Tang (CoRR, 2022)

Jointly Attacking Graph Neural Network and its Explanations. - Wenqi Fan; Han Xu 002; Wei Jin 009; Xiaorui Liu; Xianfeng Tang; Suhang Wang; Qing Li 001; Jiliang Tang; Jianping Wang 001; Charu C. Aggarwal (ICDE, 2023)

Transferable Unlearnable Examples. - Jie Ren 019; Han Xu 002; Yuxuan Wan; Xingjun Ma; Lichao Sun 001; Jiliang Tang (ICLR, 2023)

Probabilistic Categorical Adversarial Attack and Adversarial Training. - Han Xu 002; Pengfei He; Jie Ren 019; Yuxuan Wan; Zitao Liu 001; Hui Liu 031; Jiliang Tang (ICML, 2023)

How does the Memorization of Neural Networks Impact Adversarial Robust Models? - Han Xu 002; Xiaorui Liu; Wentao Wang 006; Zitao Liu 001; Anil K. Jain 001; Jiliang Tang (KDD, 2023)

Sharpness-Aware Data Poisoning Attack. - Pengfei He; Han Xu 002; Jie Ren 019; Yingqian Cui; Hui Liu 031; Charu C. Aggarwal; Jiliang Tang (CoRR, 2023)

DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models. - Yingqian Cui; Jie Ren 019; Han Xu 002; Pengfei He; Hui Liu 031; Lichao Sun 001; Jiliang Tang (CoRR, 2023)

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models. - Yingqian Cui; Jie Ren 019; Yuping Lin; Han Xu 002; Pengfei He; Yue Xing 002; Wenqi Fan; Hui Liu 031; Jiliang Tang (CoRR, 2023)

Confidence-driven Sampling for Backdoor Attacks. - Pengfei He; Han Xu 002; Yue Xing 002; Jie Ren 019; Yingqian Cui; Shenglai Zeng; Jiliang Tang; Makoto Yamada; Mohammad Sabokrou (CoRR, 2023)

Exploring Memorization in Fine-tuned Language Models. - Shenglai Zeng; Yaxin Li 001; Jie Ren 019; Yiding Liu; Han Xu 002; Pengfei He; Yue Xing 002; Shuaiqiang Wang; Jiliang Tang; Dawei Yin (ACL (1), 2024)

The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG). - Shenglai Zeng; Jiankun Zhang; Pengfei He; Yiding Liu; Yue Xing 002; Han Xu 002; Jie Ren 019; Yi Chang 001; Shuaiqiang Wang; Dawei Yin; Jiliang Tang (ACL (Findings), 2024)

Unveiling and Mitigating Memorization in Text-to-Image Diffusion Models Through Cross Attention. - Jie Ren 019; Yaxin Li 001; Shenglai Zeng; Han Xu 002; Lingjuan Lyu; Yue Xing 002; Jiliang Tang (ECCV (77), 2024)

Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis. - Yuping Lin; Pengfei He; Han Xu 002; Yue Xing 002; Makoto Yamada; Hui Liu 031; Jiliang Tang (EMNLP, 2024)

On the Generalization of Training-based ChatGPT Detection Methods. - Han Xu 002; Jie Ren 019; Pengfei He; Shenglai Zeng; Yingqian Cui; Amy Liu; Hui Liu 031; Jiliang Tang (EMNLP (Findings), 2024)

Sharpness-Aware Data Poisoning Attack. - Pengfei He; Han Xu 002; Jie Ren 019; Yingqian Cui; Shenglai Zeng; Hui Liu 031; Charu C. Aggarwal; Jiliang Tang (ICLR, 2024)

A Robust Semantics-based Watermark for Large Language Model against Paraphrasing. - Jie Ren 019; Han Xu 002; Yiding Liu; Yingqian Cui; Shuaiqiang Wang; Dawei Yin; Jiliang Tang (NAACL-HLT (Findings), 2024)

Neural Style Protection: Counteracting Unauthorized Neural Style Transfer. - Yaxin Li 001; Jie Ren 019; Han Xu 002; Hui Liu 031 (WACV, 2024)

Copyright Protection in Generative AI: A Technical Perspective. - Jie Ren 019; Han Xu 002; Pengfei He; Yingqian Cui; Shenglai Zeng; Jiankun Zhang; Hongzhi Wen; Jiayuan Ding; Hui Liu 031; Yi Chang 001; Jiliang Tang (CoRR, 2024)

Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data. - Shenglai Zeng; Jiankun Zhang; Pengfei He; Jie Ren 019; Tianqi Zheng; Hanqing Lu; Han Xu 002; Hui Liu 031; Yue Xing 002; Jiliang Tang (CoRR, 2024)

Towards the Effect of Examples on In-Context Learning: A Theoretical Case Study. - Pengfei He; Yingqian Cui; Han Xu 002; Hui Liu 031; Makoto Yamada; Jiliang Tang; Yue Xing 002 (CoRR, 2024)

Stealthy Backdoor Attack via Confidence-driven Sampling. - Pengfei He; Yue Xing 002; Han Xu 002; Jie Ren 019; Yingqian Cui; Shenglai Zeng; Jiliang Tang; Makoto Yamada; Mohammad Sabokrou (Trans. Mach. Learn. Res., 2024)

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models. - Yingqian Cui; Jie Ren 019; Yuping Lin; Han Xu 002; Pengfei He; Yue Xing 002; Lingjuan Lyu; Wenqi Fan; Hui Liu 031; Jiliang Tang (SIGKDD Explor., 2024)

DiffusionShield: A Watermark for Data Copyright Protection against Generative Diffusion Models. - Yingqian Cui; Jie Ren 019; Han Xu 002; Pengfei He; Hui Liu 031; Lichao Sun 001; Yue Xing 002; Jiliang Tang (SIGKDD Explor., 2024)

Red-Teaming LLM Multi-Agent Systems via Communication Attacks. - Pengfei He; Yuping Lin; Shen Dong; Han Xu 002; Yue Xing 002; Hui Liu 031 (ACL (Findings), 2025)

Data Poisoning for In-context Learning. - Pengfei He; Han Xu 002; Yue Xing 002; Hui Liu 031; Makoto Yamada; Jiliang Tang (NAACL (Findings), 2025)

Multi-Faceted Studies on Data Poisoning can Advance LLM Development. - Pengfei He; Yue Xing 002; Han Xu 002; Zhen Xiang; Jiliang Tang (CoRR, 2025)

Red-Teaming LLM Multi-Agent Systems via Communication Attacks. - Pengfei He; Yupin Lin; Shen Dong; Han Xu 002; Yue Xing 002; Hui Liu 031 (CoRR, 2025)

Comprehensive Vulnerability Analysis is Necessary for Trustworthy LLM-MAS. - Pengfei He; Yue Xing 002; Shen Dong; Juanhui Li; Zhenwei Dai; Xianfeng Tang; Hui Liu 031; Han Xu 002; Zhen Xiang; Charu C. Aggarwal; Hui Liu 031 (CoRR, 2025)