Graphical Evolutionary Game Theoretic Analysis of Super Users in Information Diffusion. - Yuejiang Li; Yaxin Li 001; Hong Hu; H. Vicky Zhao; Yan Chen 007 (ICASSP, 2020)

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

Elastic Graph Neural Networks. - Xiaorui Liu; Wei Jin 009; Yao Ma 001; Yaxin Li 001; Hua Liu; Yiqi Wang 001; Ming Yan 006; Jiliang Tang (ICML, 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)

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)

Trustworthy AI: A Computational Perspective. - Haochen Liu; Yiqi Wang 001; Wenqi Fan; Xiaorui Liu; Yaxin Li 001; Shaili Jain; 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 Practical Robustness Evaluation and Robustness Enhancing. - Yaxin Li 001 (WSDM, 2022)

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

A Mix-up Strategy to Enhance Adversarial Training with Imbalanced Data. - Wentao Wang 006; Harry Shomer; Yuxuan Wan; Yaxin Li 001; Jiangtao Huang; Hui Liu 031 (CIKM, 2023)

Trustworthy AI: A Computational Perspective. - Haochen Liu; Yiqi Wang 001; Wenqi Fan; Xiaorui Liu; Yaxin Li 001; Shaili Jain; Yunhao Liu 001; Anil K. Jain 001; Jiliang Tang (ACM Trans. Intell. Syst. Technol., 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)

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)

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