Provable Training for Graph Contrastive Learning. - Yue Yu 007; Xiao Wang 017; Mengmei Zhang; Nian Liu; Chuan Shi 001 (NeurIPS, 2023)

Data-centric Graph Learning: A Survey. - Cheng Yang 002; Deyu Bo; Jixi Liu; Yufei Peng; Boyu Chen; Haoran Dai; Ao Sun; Yue Yu 007; Yixin Xiao; Qi Zhang 066; Chunchen Wang; Yuxin Guo; et al. (CoRR, 2023)

Endowing Pre-trained Graph Models with Provable Fairness. - Zhongjian Zhang; Mengmei Zhang; Yue Yu 007; Cheng Yang 002; Jiawei Liu 006; Chuan Shi 001 (WWW, 2024)

GraphLoRA: Empowering LLMs Fine-Tuning via Graph Collaboration of MoE. - Ting Bai; Yue Yu 007; Le Huang; Zenan Xu; Zhe Zhao 006; Chuan Shi 001 (CoRR, 2024)

Unifying Graph Neural Networks with a Generalized Optimization Framework. - Chuan Shi 001; Meiqi Zhu; Yue Yu 007; Xiao Wang 017; Junping Du 001 (ACM Trans. Inf. Syst., 2024)

Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks? - Zhongjian Zhang; Xiao Wang 017; Huichi Zhou; Yue Yu 007; Mengmei Zhang; Cheng Yang 002; Chuan Shi 001 (KDD (1), 2025)

Efficient Multi-task Prompt Tuning for Recommendation. - Ting Bai; Le Huang; Yue Yu 007; Cheng Yang 002; Cheng Hou; Zhe Zhao 006; Chuan Shi 001 (ACM Trans. Inf. Syst., 2025)