Leveraging Free Labels to Power up Heterophilic Graph Learning in Weakly-Supervised Settings: An Empirical Study. - Xugang Wu; Huijun Wu 001; Ruibo Wang; Duanyu Li; Xu Zhou 004; Kai Lu 001 (ECML/PKDD (3), 2023)

Talos: A More Effective and Efficient Adversarial Defense for GNN Models Based on the Global Homophily of Graphs. - Duanyu Li; Huijun Wu 001; Min Xie; Xugang Wu; Zhenwei Wu; Wenzhe Zhang (ECAI, 2024)

Exploiting Global Graph Homophily for Generalized Defense in Graph Neural Networks. - Duanyu Li; Huijun Wu 001; Min Xie; Xugang Wu; Zhenwei Wu; Wenzhe Zhang (CoRR, 2024)

Perseus: Leveraging Common Data Patterns with Curriculum Learning for More Robust Graph Neural Networks. - Kaiwen Xia; Huijun Wu 001; Duanyu Li; Min Xie; Ruibo Wang; Wenzhe Zhang (CoRR, 2024)