| 2026 | SIGIR | Hierarchical Cluster-based Open-World Graph Active Learning. | Yayong Li, Zhengyi Du, Hong Zhang, Jonathan Wilton, Jinran Wu, Zongli Liu, Nan Ye |
| 2025 | KDD | Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning. | Xinyi Gao, Yayong Li, Tong Chen, Guanhua Ye, Wentao Zhang, Hongzhi Yin |
| 2025 | PRICAI | Generalized Few-Shot Node Classification via Training Set Refinement. | Yayong Li, Xubo Zhang, Hong Zhang, Nan Ye, Zongli Liu, Jinran Wu |
| 2025 | WSDM | Inductive Graph Few-shot Class Incremental Learning. | Yayong Li, Peyman Moghadam, Can Peng, Nan Ye, Piotr Koniusz |
| 2024 | KDD | Graph Condensation for Open-World Graph Learning. | Xinyi Gao, Tong Chen, Wentao Zhang, Yayong Li, Xiangguo Sun, Hongzhi Yin |
| 2022 | CSCWD | Attentive Feature Fusion for Credit Default Prediction. | Ximing Liu, Yayong Li, Cuiqing Jiang, Zhao Wang, Fuqing Zhao, Jianfei Wang |
| 2022 | ICLR | Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective. | Wei Huang, Yayong Li, Weitao Du, Richard Y. D. Xu, Jie Yin, Ling Chen, Miao Zhang |
| 2021 | PAKDD | Unified Robust Training for Graph Neural Networks Against Label Noise. | Yayong Li, Jie Yin, Ling Chen |
| 2016 | DASC | Fast CU Size Decisions for HEVC Intra Frame Coding Based on Support Vector Machines. | Deyuan Liu, Xingang Liu, Yayong Li |