Label-Wise Message Passing Graph Neural Network on Heterophilic Graphs. - Enyan Dai; Zhimeng Guo; Suhang Wang (CoRR, 2021)

Label-Wise Graph Convolutional Network for Heterophilic Graphs. - Enyan Dai; Shijie Zhou; Zhimeng Guo; Suhang Wang (LoG, 2022)

Decoupled Self-supervised Learning for Graphs. - Teng Xiao; Zhengyu Chen 001; Zhimeng Guo; Zeyang Zhuang; Suhang Wang (NeurIPS, 2022)

Decoupled Self-supervised Learning for Non-Homophilous Graphs. - Teng Xiao; Zhengyu Chen 001; Zhimeng Guo; Zeyang Zhuang; Suhang Wang (CoRR, 2022)

Link Prediction on Heterophilic Graphs via Disentangled Representation Learning. - Shijie Zhou; Zhimeng Guo; Charu C. Aggarwal; Xiang Zhang 001; Suhang Wang (CoRR, 2022)

Towards Fair Graph Neural Networks via Graph Counterfactual. - Zhimeng Guo; Jialiang Li 003; Teng Xiao; Yao Ma 001; Suhang Wang (CIKM, 2023)

Counterfactual Learning on Graphs: A Survey. - Zhimeng Guo; Teng Xiao; Charu Aggarwal 001; Hui Liu 031; Suhang Wang (CoRR, 2023)

Fairness-aware Message Passing for Graph Neural Networks. - Huaisheng Zhu; Guoji Fu; Zhimeng Guo; Zhiwei Zhang; Teng Xiao; Suhang Wang (CoRR, 2023)

Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective. - Zhimeng Guo; Jialiang Li 003; Teng Xiao; Yao Ma 001; Suhang Wang (CoRR, 2023)

On the Safety of Open-Sourced Large Language Models: Does Alignment Really Prevent Them From Being Misused? - Hangfan Zhang; Zhimeng Guo; Huaisheng Zhu; Bochuan Cao; Lu Lin 001; Jinyuan Jia 001; Jinghui Chen; Dinghao Wu (CoRR, 2023)

Jailbreak Open-Sourced Large Language Models via Enforced Decoding. - Hangfan Zhang; Zhimeng Guo; Huaisheng Zhu; Bochuan Cao; Lu Lin 001; Jinyuan Jia 001; Jinghui Chen; Dinghao Wu (ACL (1), 2024)

Efficient Contrastive Learning for Fast and Accurate Inference on Graphs. - Teng Xiao; Huaisheng Zhu; Zhiwei Zhang; Zhimeng Guo; Charu C. Aggarwal; Suhang Wang; Vasant G. Honavar (ICML, 2024)

Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. - Xiaowei Qian; Zhimeng Guo; Jialiang Li 003; Haitao Mao; Bingheng Li; Suhang Wang; Yao Ma 001 (KDD, 2024)

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. - Enyan Dai; Tianxiang Zhao 001; Huaisheng Zhu; Junjie Xu; Zhimeng Guo; Hui Liu 031; Jiliang Tang; Suhang Wang (Mach. Intell. Res., 2024)

Counterfactual Learning on Graphs: A Survey. - Zhimeng Guo; Zongyu Wu 001; Teng Xiao; Charu Aggarwal 001; Hui Liu 031; Suhang Wang (Mach. Intell. Res., 2025)