Bringing Graphs to the Table: Zero-shot Node Classification via Tabular Foundation Models
Fuente:
arXiv
Saved in:
| Main Authors: | Hayler, Adrian, Huang, Xingyue, Ceylan, İsmail İlkan, Bronstein, Michael, Finkelshtein, Ben |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Cooperative Graph Neural Networks
by: Finkelshtein, Ben, et al.
Published: (2023)
by: Finkelshtein, Ben, et al.
Published: (2023)
Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models
by: Finkelshtein, Ben, et al.
Published: (2025)
by: Finkelshtein, Ben, et al.
Published: (2025)
Learning on Large Graphs using Intersecting Communities
by: Finkelshtein, Ben, et al.
Published: (2024)
by: Finkelshtein, Ben, et al.
Published: (2024)
HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphs
by: Huang, Xingyue, et al.
Published: (2025)
by: Huang, Xingyue, et al.
Published: (2025)
Flock: A Knowledge Graph Foundation Model via Learning on Random Walks
by: Kim, Jinwoo, et al.
Published: (2025)
by: Kim, Jinwoo, et al.
Published: (2025)
Almost Surely Asymptotically Constant Graph Neural Networks
by: Adam-Day, Sam, et al.
Published: (2024)
by: Adam-Day, Sam, et al.
Published: (2024)
How Expressive are Knowledge Graph Foundation Models?
by: Huang, Xingyue, et al.
Published: (2025)
by: Huang, Xingyue, et al.
Published: (2025)
One Model, Any Conjunctive Query: Graph Neural Networks for Answering Queries over Incomplete Knowledge Graphs
by: Olejniczak, Krzysztof, et al.
Published: (2024)
by: Olejniczak, Krzysztof, et al.
Published: (2024)
Homomorphism Counts for Graph Neural Networks: All About That Basis
by: Jin, Emily, et al.
Published: (2024)
by: Jin, Emily, et al.
Published: (2024)
Link Prediction with Relational Hypergraphs
by: Huang, Xingyue, et al.
Published: (2024)
by: Huang, Xingyue, et al.
Published: (2024)
Homomorphism Counts as Structural Encodings for Graph Learning
by: Bao, Linus, et al.
Published: (2024)
by: Bao, Linus, et al.
Published: (2024)
Zero-One Laws of Graph Neural Networks
by: Adam-Day, Sam, et al.
Published: (2023)
by: Adam-Day, Sam, et al.
Published: (2023)
RelAgent: LLM Agents as Data Scientists for Relational Learning
by: Huang, Xingyue, et al.
Published: (2026)
by: Huang, Xingyue, et al.
Published: (2026)
MacroGuide: Topological Guidance for Macrocycle Generation
by: Maksymiuk, Alicja, et al.
Published: (2026)
by: Maksymiuk, Alicja, et al.
Published: (2026)
Fisher Flow Matching for Generative Modeling over Discrete Data
by: Davis, Oscar, et al.
Published: (2024)
by: Davis, Oscar, et al.
Published: (2024)
Efficient Learning on Large Graphs using a Densifying Regularity Lemma
by: Kouchly, Jonathan, et al.
Published: (2025)
by: Kouchly, Jonathan, et al.
Published: (2025)
What are the Right Symmetries for Formal Theorem Proving?
by: Olejniczak, Krzysztof, et al.
Published: (2026)
by: Olejniczak, Krzysztof, et al.
Published: (2026)
Curly Flow Matching for Learning Non-gradient Field Dynamics
by: Petrović, Katarina, et al.
Published: (2025)
by: Petrović, Katarina, et al.
Published: (2025)
Fully-inductive Node Classification on Arbitrary Graphs
by: Zhao, Jianan, et al.
Published: (2024)
by: Zhao, Jianan, et al.
Published: (2024)
Categorical Flow Maps
by: Roos, Daan, et al.
Published: (2026)
by: Roos, Daan, et al.
Published: (2026)
Future Directions in the Theory of Graph Machine Learning
by: Morris, Christopher, et al.
Published: (2024)
by: Morris, Christopher, et al.
Published: (2024)
Can TabPFN Compete with GNNs for Node Classification via Graph Tabularization?
by: Choi, Jeongwhan, et al.
Published: (2025)
by: Choi, Jeongwhan, et al.
Published: (2025)
FoMo-0D: A Foundation Model for Zero-shot Tabular Outlier Detection
by: Shen, Yuchen, et al.
Published: (2024)
by: Shen, Yuchen, et al.
Published: (2024)
Turning Tabular Foundation Models into Graph Foundation Models
by: Eremeev, Dmitry, et al.
Published: (2025)
by: Eremeev, Dmitry, et al.
Published: (2025)
Can Graph Foundation Models Generalize Over Architecture?
by: Gutteridge, Benjamin, et al.
Published: (2026)
by: Gutteridge, Benjamin, et al.
Published: (2026)
Can Graphs Improve Tabular Foundation Models?
by: Le, Franck, et al.
Published: (2025)
by: Le, Franck, et al.
Published: (2025)
Understanding Virtual Nodes: Oversquashing and Node Heterogeneity
by: Southern, Joshua, et al.
Published: (2024)
by: Southern, Joshua, et al.
Published: (2024)
ZEUS: Zero-shot Embeddings for Unsupervised Separation of Tabular Data
by: Marszałek, Patryk, et al.
Published: (2025)
by: Marszałek, Patryk, et al.
Published: (2025)
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection
by: Qiao, Hezhe, et al.
Published: (2025)
by: Qiao, Hezhe, et al.
Published: (2025)
TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models
by: Grinsztajn, Léo, et al.
Published: (2025)
by: Grinsztajn, Léo, et al.
Published: (2025)
From Zero to Hero: Advancing Zero-Shot Foundation Models for Tabular Outlier Detection
by: Ding, Xueying, et al.
Published: (2026)
by: Ding, Xueying, et al.
Published: (2026)
Tabular Foundation Models are Strong Graph Anomaly Detectors
by: Liu, Yunhui, et al.
Published: (2026)
by: Liu, Yunhui, et al.
Published: (2026)
On the Uncertainty Quantification Ability of Tabular Foundation Models
by: Johnson, Tyler R., et al.
Published: (2026)
by: Johnson, Tyler R., et al.
Published: (2026)
iN2V: Bringing Transductive Node Embeddings to Inductive Graphs
by: Lell, Nicolas, et al.
Published: (2025)
by: Lell, Nicolas, et al.
Published: (2025)
Theoretical Insights into Line Graph Transformation on Graph Learning
by: Yang, Fan, et al.
Published: (2024)
by: Yang, Fan, et al.
Published: (2024)
TabularFM: An Open Framework For Tabular Foundational Models
by: Tran, Quan M., et al.
Published: (2024)
by: Tran, Quan M., et al.
Published: (2024)
On Finetuning Tabular Foundation Models
by: Rubachev, Ivan, et al.
Published: (2025)
by: Rubachev, Ivan, et al.
Published: (2025)
PUMA: Efficient Continual Graph Learning for Node Classification with Graph Condensation
by: Liu, Yilun, et al.
Published: (2023)
by: Liu, Yilun, et al.
Published: (2023)
Zero-shot Imputation with Foundation Inference Models for Dynamical Systems
by: Seifner, Patrick, et al.
Published: (2024)
by: Seifner, Patrick, et al.
Published: (2024)
A Foundation Model for Zero-shot Logical Query Reasoning
by: Galkin, Mikhail, et al.
Published: (2024)
by: Galkin, Mikhail, et al.
Published: (2024)
Similar Items
-
Cooperative Graph Neural Networks
by: Finkelshtein, Ben, et al.
Published: (2023) -
Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models
by: Finkelshtein, Ben, et al.
Published: (2025) -
Learning on Large Graphs using Intersecting Communities
by: Finkelshtein, Ben, et al.
Published: (2024) -
HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphs
by: Huang, Xingyue, et al.
Published: (2025) -
Flock: A Knowledge Graph Foundation Model via Learning on Random Walks
by: Kim, Jinwoo, et al.
Published: (2025)