Publications

Tutorials

Zhichao Hou, Minhua Lin, MohamadAli Torkamani, Suhang Wang, Xiaorui Liu. “Adversarial Robustness in Graph Neural Networks: Recent Advances and New Frontier” In 11th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2024) [paper]

Minhua Lin, Hui Liu, Xianfeng Tang, Jingying Zeng, Zhenwei Dai, Chen Luo, Zheng Li, Xiang Zhang, Qi He, Suhang Wang. “How Far are LLMs from Real Search? A Comprehensive Study on Efficiency, Completeness, and Inherent Capabilities” [paper]
Minhua Lin, Zhengzhang Chen, Yanchi Liu, Xujiang Zhao, Zongyu Wu, Junxiang Wang, Xiang Zhang, Suhang Wang, Haifeng Cheng. “Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotation” [paper]
Minhua Lin*, Zhiwei Zhang*, Enyan Dai, Zongyu Wu, Yilong Wang, Xiang Zhang, Suhang Wang (* indicates equal contribution). “Trojan Prompt Attacks on Graph Neural Networks” [paper, code]
Enyan Dai*, Minhua Lin*, Suhang Wang (* indicates equal contribution). “PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection” [paper, code]
Zongyu Wu*, Yuwei Niu*, Hongcheng Gao, Minhua Lin, Zhiwei Zhang, Zhifang Zhang, Qi Shi, Yilong Wang, Sike Fu, Junjie Xu, Junjie Ao, Enyan Dai, Lei Feng, Xiang Zhang, Suhang Wang (* indicates equal contribution). “LanP: Rethinking the Impact of Language Priors in Large Vision-Language Models” [paper, code, project page]
Junjie Xu, Zongyu Wu, Minhua Lin, Xiang Zhang, Suhang Wang. “LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning” [paper]

Minhua Lin, Enyan Dai, Junjie Xu, Jinyuan Jia, Xiang Zhang, Suhang Wang. “Stealing Training Graphs from Graph Neural Networks” In 31th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025) [paper, code]
Zhiwei Zhang, Minhua Lin, Junjie Xu, Zongyu Wu, Enyan Dai, Suhang Wang. “Robustness-Inspired Defense Against Backdoor Attacks on Graph Neural Networks” In 13th International Conference on Learning Representations (ICLR 2025) [paper]
Zhengpin Li, Minhua Lin, Jian Wang, Suhang Wang. “Fairness-aware Prompt Tuning for Graph Neural Networks” In Proceedings of the ACM Web Conference 2025 (WWW 2025) [paper]

Binghui Wang*, Minhua Lin*, Tianxiang Zhou, Pan Zhou, Ang Li, Meng Pang, Cai Fu, Hai Li, Yiran Chen (* indicates equal contribution). “Efficient, Direct, and Restricted Black-Box Graph Evasion Attacks to Any-Layer Graph Neural Networks via Influence Function” In 17th ACM International Conference on Web Search and Data Mining (WSDM 2024) [paper, code]
Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang. “Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective” In 30th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024) [paper, code]

Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang. “Certifiably Robust Graph Contrastive Learning” In Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023) [paper, code]
Enyan Dai*, Minhua Lin*, Xiang Zhang, Suhang Wang (* indicates equal contribution). “Unnoticeable Backdoor Attacks on Graph Neural Networks” In Proceedings of the ACM Web Conference 2023 (WWW 2023) [paper, code]