Title：Beyond Words: Riemannian Geometry for Next-Generation Graph Foundation Models
Date：2026/07/13 14:00-16:00
Location：博理館 BL101Date：2026/07/13 14:00-16:00
Speaker：Prof. Philip S. Yu
Host：Prof. Ming-Syan Chen
Abstract:
Graph Foundation Models (GFMs) are poised to transform graph learning, yet substantial debate remains over how to construct a general-purpose GFM analogous to Large Language Models (LLMs). Traditional Graph Neural Networks (GNNs) struggle with memory retention, principled interpretability, and multi-domain adaptation, while graph serialization limits the direct application of LLMs, as linear tokens fail to capture the rich structural complexity of graphs. In contrast, Riemannian geometry provides a natural, mathematically principled framework for modeling graph structures, offering compatibility with semantic graph learning and LLM integration. In this talk, we argue that for graphs, geometry speaks louder than words. We introduce Riemannian Graph Foundations, which prioritize intrinsic graph geometry and endow models with endogenous capabilities for structural inference and generation, moving beyond simple representation-space transformations. Recent results on building a graph foundation model within Riemannian geometric space will be presented, highlighting how this approach lays the groundwork for next-generation graph intelligence.
Bio:
Philip S. Yu's main research interests include big data, data mining (especially on graph/network mining), social network, privacy preserving data publishing, data stream, database systems, and Internet applications and technologies. He is a Disthinguished Professor in the Department of Computer Science at UIC and also holds the Wexler Chair in Information and Technology. Before joining UIC, he was with IBM Thomas J. Watson Research Center, where he was manager of the Software Tools and Techniques department. Dr. Yu has published more than 970 papers in refereed journals and conferences with more than 74,500 citations and an H-index of 127. He holds or has applied for more than 300 US patents.