☕️Xingtong Yu now is a Ph.D. candidate in the University of Science and Technology of China. His research interests lie in graph learning and prompt tuning, particularly in investigating the novel research problems such as learning on heterogeneous information network and dynamic graphs, few-shot learning. Moreover, he has served as the PC member for top-tier conferences including ICLR, NeurIPS, ICML, etc.
Education
Experiences
Visiting Research Student
Featured Papers
Recent Papers
(2024).
Text-Free Multi-domain Graph Pre-training: Toward Graph Foundation Models.
Under review.
(2024).
DyGPrompt: Learning Feature and Time Prompts on Dynamic Graphs .
Under review.
(2023).
MultiGPrompt for Multi-Task Pre-Training and Prompting on Graphs.
The ACM Web Conference (WWW), 2024.
(2023).
HGPrompt: Bridging Homogeneous and Heterogeneous Graphs for Few-shot Prompt Learning.
The AAAI Conference on Artificial Intelligence (AAAI), 2024.
Academic Service
Program Committee Member
- NeurIPS (2023, 2024)
- ICLR (2024)
- ICML (2024)
- WWW (2024)
- CVPR (2024)
- ICMR (2024)
- CIKM (2024)
Journal Reviewer
- Frontiers of Computer Science
- PeerJ Computer Science