Publications

Xingtong Yu, Zhenghao Liu, Yuan Fang, Zemin Liu, Sihong Chen, Xinming Zhang (2024). Generalized Graph Prompt: Toward a Unification of Pre-Training and Downstream Tasks on Graphs. IEEE Transactions on Knowledge and Data Engineering.

Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhang (2024). Text-Free Multi-domain Graph Pre-training: Toward Graph Foundation Models. Under review.

Xingtong Yu, Zhenghao Liu, Yuan Fang, Xinming Zhang (2024). DyGPrompt: Learning Feature and Time Prompts on Dynamic Graphs . Under review.

Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhang (2024). MultiGPrompt for Multi-Task Pre-Training and Prompting on Graphs. The ACM Web Conference (WWW), 2024.

Xingtong Yu, Yuan Fang, Zemin Liu, Yuxia Wu, Zhihao Wen, Jianyuan Bo, Xinming Zhang, Steven C.H. Hoi (2024). Few-Shot Learning on Graphs: from Meta-learning to Pre-training and Prompting. Preprint.

Xingtong Yu, Yuan Fang, Zemin Liu, Xinming Zhang (2024). HGPrompt: Bridging Homogeneous and Heterogeneous Graphs for Few-shot Prompt Learning. The AAAI Conference on Artificial Intelligence (AAAI), 2024.

Peng Xia, Xingtong Yu, Ming Hu, Lie Ju, Zhiyong Wang, Peibo Duan, Zongyuan Ge (2023). HGCLIP: Exploring Vision-Language Models with Graph Representations for Hierarchical Understanding. Under review.

Wenyu Zhang, Xin Deng, Baojun Jia, Xingtong Yu, Yifan Chen, jin Ma, Qing Ding, Xinming Zhang (2023). Pixel Adapter: A Graph-Based Post-Processing Approach for Scene Text Image Super-Resolution. The ACM International Conference on Multimedia (ACMMM), 2023.

Zemin Liu, Xingtong Yu, Yuan Fang, Xinming Zhang (2023). GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks. The ACM Web Conference (WWW), 2023.

Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang (2023). Learning to Count Isomorphisms with Graph Neural Networks. The AAAI Conference on Artificial Intelligence (AAAI), 2023.