4 papers
Out-of-Distribution Generalization in Graph Foundation Models
Haoyang Li, Haibo Chen, Xin Wang +1
Graphs are a fundamental data structure for representing relational information in domains such as social networks, molecular systems, and knowledge graphs. However, graph learning…
Modular Machine Learning: An Indispensable Path towards New-Generation Large Language Models
Xin Wang, Haoyang Li, Haibo Chen +2
Large language models (LLMs) have substantially advanced machine learning research, including natural language processing, computer vision, data mining, etc., yet they still exhibi…
LLM4DyG: Can Large Language Models Solve Spatial-Temporal Problems on Dynamic Graphs?
Zeyang Zhang, Xin Wang, Ziwei Zhang +3
In an era marked by the increasing adoption of Large Language Models (LLMs) for various tasks, there is a growing focus on exploring LLMs' capabilities in handling web data, partic…
Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and Directions
Xin Wang, Ziwei Zhang, Haoyang Li +1
Graph machine learning has been extensively studied in both academic and industry. However, as the literature on graph learning booms with a vast number of emerging methods and tec…