Friend Recommendations with Self-Rescaling Graph Neural Networks. - Xiran Song; Jianxun Lian; Hong Huang 001; Mingqi Wu; Hai Jin 001; Xing Xie 001 (KDD, 2022)

Cross-links Matter for Link Prediction: Rethinking the Debiased GNN from a Data Perspective. - Zihan Luo 001; Hong Huang 001; Jianxun Lian; Xiran Song; Xing Xie 001; Hai Jin 001 (NeurIPS, 2023)

xGCN: An Extreme Graph Convolutional Network for Large-scale Social Link Prediction. - Xiran Song; Jianxun Lian; Hong Huang 001; Zihan Luo 001; Wei Zhou; Xue Lin 005; Mingqi Wu; Chaozhuo Li; Xing Xie 001; Hai Jin 001 (WWW, 2023)

Temporal Heterogeneous Information Network Embedding via Semantic Evolution. - Wei Zhou; Hong Huang 001; Ruize Shi; Xiran Song; Xue Lin 005; Xiao Wang 017; Hai Jin 001 (IEEE Trans. Knowl. Data Eng., 2023)

GraphInstruct: Empowering Large Language Models with Graph Understanding and Reasoning Capability. - Zihan Luo 001; Xiran Song; Hong Huang 001; Jianxun Lian; Chenhao Zhang 005; Jinqi Jiang; Xing Xie 001 (CoRR, 2024)

XGCN: a library for large-scale graph neural network recommendations. - Xiran Song; Hong Huang 001; Jianxun Lian; Hai Jin 001 (Frontiers Comput. Sci., 2024)

Towards Controllable Hybrid Fairness in Graph Neural Networks. - Zihan Luo 001; Hong Huang 001; Jianxun Lian; Xiran Song; Hai Jin 001 (KDD (1), 2025)