Zehong-Wang/Awesome-Foundation-Models-on-Graphs
A collection of graph foundation models including papers, codes, and datasets.
This resource collects information on Graph Foundation Models (GFMs), which are advanced AI models designed to understand and work with complex networked data like social connections, web links, or molecular structures. It provides researchers with a curated list of papers, code, and datasets related to these models. Scientists, researchers, and data practitioners working with graph-structured data would use this to find foundational models that can generalize across various tasks and domains.
178 stars. No commits in the last 6 months.
Use this if you are a researcher or practitioner exploring the latest advancements in AI for complex networked data, specifically looking for general-purpose models that can be adapted to various graph-related tasks across different domains.
Not ideal if you are looking for ready-to-use software applications or a beginner's introduction to graph theory, as this resource focuses on academic research and cutting-edge model development.
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Jul 10, 2025
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