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This tutorial will help researchers and practitioners from the database and data management community understand the major implementation paths and open problems in Graph Foundation Models.
GraphAgent is demonstrated, a user-friendly and effective system for knowledge-guided selection of Graph Neural Network models for new graph data that unifies over 413,000 performance records from public GNN benchmarks into a comprehensive Graph-Model Knowledge Graph (GMKG).
PolyUQuest is presented, a verifiable, structure-aware web RAG framework built on a heterogeneous graph that unifies hyperlink topology between pages, DOM hierarchy within pages, and entity-relation knowledge across pages.
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