4 papers
Decoupled and Divergence-Conditioned Prompt for Multi-domain Dynamic Graph Foundation Models
Haonan Yuan, Qingyun Sun, Junhua Shi +3
Dynamic graphs are ubiquitous in real-world systems, and building generalizable dynamic Graph Foundation Models has become a frontier in graph learning. However, dynamic graphs fro…
SAGFM: Enhancing Robust Graph Foundation Models with Structure-Aware Semantic Augmentation
Junhua Shi, Qingyun Sun, Haonan Yuan +1
We present Graph Foundation Models (GFMs) which have made significant progress in various tasks, but their robustness against domain noise, structural perturbations, and adversaria…
Retrieving Minimal and Sufficient Reasoning Subgraphs with Graph Foundation Models for Path-aware GraphRAG
Haonan Yuan, Qingyun Sun, Junhua Shi +5
Graph-based retrieval-augmented generation (GraphRAG) exploits structured knowledge to support knowledge-intensive reasoning. However, most existing methods treat graphs as interme…
GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning
Haonan Yuan, Qingyun Sun, Junhua Shi +4
Inspired by the remarkable success of foundation models in language and vision, Graph Foundation Models (GFMs) hold significant promise for broad applicability across diverse graph…