NeurIPS 2025 "graph foundation models" Papers
8 papers found
Deeper with Riemannian Geometry: Overcoming Oversmoothing and Oversquashing for Graph Foundation Models
Li Sun, Zhenhao Huang, Ming Zhang et al.
NeurIPS 2025posterarXiv:2510.17457
1
citations
Enhanced Expert Merging for Mixture-of-Experts in Graph Foundation Models
Lei Liu, Xingyu Xia, Qianqian Xie et al.
NeurIPS 2025poster
Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models
Ben Finkelshtein, Ismail Ilkan Ceylan, Michael Bronstein et al.
NeurIPS 2025posterarXiv:2506.14291
10
citations
Flatten Graphs as Sequences: Transformers are Scalable Graph Generators
Dexiong Chen, Markus Krimmel, Karsten Borgwardt
NeurIPS 2025posterarXiv:2502.02216
4
citations
GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data
Gleb Bazhenov, Oleg Platonov, Liudmila Prokhorenkova
NeurIPS 2025oralarXiv:2409.14500
7
citations
GraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments
Enjun Du, Xunkai Li, Tian Jin et al.
NeurIPS 2025spotlightarXiv:2504.00711
17
citations
GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning
Haonan Yuan, Qingyun Sun, Junhua Shi et al.
NeurIPS 2025posterarXiv:2511.05592
3
citations
The Underappreciated Power of Vision Models for Graph Structural Understanding
Xinjian Zhao, Wei Pang, Zhongkai Xue et al.
NeurIPS 2025posterarXiv:2510.24788
1
citations