Publications
Research highlights can be found here.
BiMark: Unbiased Multilayer Watermarking for Large Language Models. [Paper]
Xiaoyan Feng†, He Zhang†, Yanjun Zhang, Leo Yu Zhang, Shirui Pan.
International Conference on Machine Learning (ICML), 2025. (CORE A*, Acceptance rate 26.9%, †co-first author, )
Dynamic Graph Unlearning: A General and Efficient Post-Processing Method via Gradient Transformation. [Paper]
He Zhang, Bang Wu, Xiangwen Yang, Xingliang Yuan, Xiaoning Liu, Xun Yi .
ACM International World Wide Web Conference (WWW), 2025. (CORE A*, Oral, Acceptance rate 19.84%)
Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks. [Paper]
He Zhang, Xingliang Yuan, Shirui Pan.
IEEE International Conference on Data Engineering (ICDE), 2024. (CORE A*, Acceptance rate 22.75%)
Trustworthy Graph Neural Networks: Aspects, Methods, and Trends. [Paper] [Resources]
He Zhang, Bang Wu, Xingliang Yuan, Shirui Pan, Hanghang Tong, Jian Pei.
Proceedings of the IEEE, 2024. (CCF A, SJR Q1, Impact factor 25.9, Issue cover)
GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks. [Paper]
Bang Wu, He Zhang, Xiangwen Yang, Shuo Wang, Minhui Xue, Shirui Pan, Xingliang Yuan.
The Network and Distributed System Security Symposium (NDSS), 2024. (CORE A*, Oral, Acceptance rate 15.0%)
GOODAT: Towards Test-time Graph Out-of-Distribution Detection. [Paper]
Luzhi Wang, Dongxiao He, He Zhang, Yixin Liu, Wenjie Wang, Shirui Pan, Di Jin, Tat-Seng Chua.
AAAI Conference on Artificial Intelligence (AAAI), 2024. (CORE A*, Oral, Acceptance rate 23.75%)
Demystifying Uneven Vulnerability of Link Stealing Attacks against Graph Neural Networks. [Paper]
He Zhang, Bang Wu, Shuo Wang, Xiangwen Yang, Minhui Xue, Shirui Pan, Xingliang Yuan.
International Conference on Machine Learning (ICML), 2023. (CORE A*, Acceptance rate 27.9%)
Finding the Missing-half: Graph Complementary Learning. [Paper]
Yizhen Zheng, He Zhang, Vincent Lee, Yu Zheng, Xiao Wang, Shirui Pan.
International Conference on Machine Learning (ICML), 2023. (CORE A*, Acceptance rate 27.9%)
A Survey on Fairness-aware Recommender Systems. [Paper]
Di Jin, Luzhi Wang, He Zhang, Yizhen Zheng, Weiping Ding, Feng Xia, Shirui Pan.
Information Fusion, 2023. (CORE B, Impact factor 18.6)
Projective Ranking-based GNN Evasion Attacks. [Paper]
He Zhang, Xingliang Yuan, Chuan Zhou, Shirui Pan.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022. (CORE A*, Impact factor 8.9)
The construction and application of integral invariants and differential invariants of graphics and images. [Paper]
Hanlin Mo, You Hao, Rui Guo, Hongxiang Hao, He Zhang, Qi Li, Hua Li.
Journal of Graphics, 2022.
Projective Ranking: A Transferable Evasion Attack Method on Graph Neural Networks. [Paper]
He Zhang, Bang Wu, Xiangwen Yang, Chuan Zhou, Shuo Wang, Xingliang Yuan, Shirui Pan.
ACM International Conference on Information and Knowledge Management (CIKM), 2021. (CORE A, Acceptance rate 21.7%)
Fast and efficient calculations of structural invariants of chirality. [Paper]
He Zhang, Hanlin Mo, You Hao, Shirui Li, Hua Li.
Pattern Recognition Letters, 2019.
Differential and integral invariants under Möbius transformation. [Paper]
He Zhang, Hanlin Mo, You Hao, Qi Li, Hua Li.
Pattern Recognition and Computer Vision (PRCV), 2018.
AMI-Net: convolution neural networks with affine moment invariants. [Paper]
You Hao, Qi Li, Hanlin Mo, He Zhang, Hua Li.
IEEE Signal Processing Letters, 2018.
A rotation invariant descriptor using multi-directional and high-order gradients. [Paper]
Hanlin Mo, Qi Li, You Hao, He Zhang, Hua Li.
Pattern Recognition and Computer Vision (PRCV), 2018.
Dual affine moment invariants. [Paper]
You Hao, Hanlin Mo, Qi Li, He Zhang, Hua Li.
Preprint.