Yifei Sun

I am a final-year CS Ph.D. student at Zhejiang University, fortunately advised by Prof. Yang Yang. Previously, I visited National University of Singapore (NUS) from Nov 2023 to Jun 2024. (working with Prof. Bingsheng He, Prof. Bryan Hooi and Prof. Zemin Liu).

My current research interests lie primarily in the area of Machine Learning and Data Mining on Graphs, including but not limited to graph neural networks, graph pre-training, and real-world applications on graphs. Moreover, in this era of LLMs, I am dedicated to building Graph Foundation Models (GFMs) and developing specialized graph LLMs.

⭐️ The main goal of my Ph.D. research is to build generalizable graph models and frameworks, capable of learning from rich and complex graph data and enhancing their utility across diverse downstream tasks and datasets.

Ongoing Work

• [🌏Generalization at the Graph Principle Level] Towards Graph Foundation Model across Domains.
• [💡Generalization at the Graph Task Level] Graph LLM for Zero-Shot Multi-Label Node Classification.
• [💡Generalization at the Graph Task Level] Tackling Multi-label Node Classification. (Under Review)

If interested, please drop me a message by email.

News

• [2024.5] Our paper “G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering” is released on Arxiv.
• [2024.5] Our paper “Chromosomal Structural Abnormality Diagnosis by Homologous Similarity” is accepted by KDD 2024 (ADS). Congrats to Juren Li!
• [2024.5] Our paper “Exploring Correlations of Self-supervised Tasks for Graphs” is accepted by ICML 2024. Congrats to Taoran Fang!

Selected Publications (Full version see Google Scholar)

Narrow the Gap between Graph Pre-training and Fine-tuning

[🎈Generalization at the Graph Data Level]

• Yifei Sun, Qi Zhu, Yang Yang, Chunping Wang, Tianyu Fan, Jiajun Zhu, Lei Chen. Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI’24), 2024.

Break the limitation of GNNs on graph data homophily

[🎈Generalization at the Graph Data Level]

• Yifei Sun, Haoran Deng, Yang Yang, Chunping Wang, Jiarong Xu, Renhong Huang, Linfeng Cao, Yang Wang, and Lei Chen. Beyond Homophily: Structure-aware Path Aggregation Graph Neural Network. In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI’22), 2022.

Academic Activities

• [2024.5] Co-organized the full-day workshop on Graph Foundation Models at the WebConf 2024.