Copertina

Position: Graph Foundation Models are Already Here

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Mao, Haitao, Chen, Zhikai, Tang, Wenzhuo, Zhao, Jianan, Ma, Yao, Zhao, Tong, Shah, Neil, Galkin, Mikhail, Tang, Jiliang
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Towards Neural Scaling Laws on Graphs
di: Liu, Jingzhe, et al.
Pubblicazione: (2024)

One Model for One Graph: A New Perspective for Pretraining with Cross-domain Graphs
di: Liu, Jingzhe, et al.
Pubblicazione: (2024)

A Pre-training Framework for Relational Data with Information-theoretic Principles
di: Truong, Quang, et al.
Pubblicazione: (2025)

Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models
di: Tang, Wenzhuo, et al.
Pubblicazione: (2024)

Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
di: Chen, Zhikai, et al.
Pubblicazione: (2024)

Fully-inductive Node Classification on Arbitrary Graphs
di: Zhao, Jianan, et al.
Pubblicazione: (2024)

LPFormer: An Adaptive Graph Transformer for Link Prediction
di: Shomer, Harry, et al.
Pubblicazione: (2023)

Label-free Node Classification on Graphs with Large Language Models (LLMS)
di: Chen, Zhikai, et al.
Pubblicazione: (2023)

A Foundation Model for Zero-shot Logical Query Reasoning
di: Galkin, Mikhail, et al.
Pubblicazione: (2024)

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
di: Chen, Zhikai, et al.
Pubblicazione: (2023)

Unveiling Mode Connectivity in Graph Neural Networks
di: Li, Bingheng, et al.
Pubblicazione: (2025)

Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness
di: Guo, Kai, et al.
Pubblicazione: (2024)

Graph Machine Learning in the Era of Large Language Models (LLMs)
di: Wang, Shijie, et al.
Pubblicazione: (2024)

Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization
di: Zhang, Qingyang, et al.
Pubblicazione: (2025)

Sub-graph Based Diffusion Model for Link Prediction
di: Li, Hang, et al.
Pubblicazione: (2024)

Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks
di: Xue, Rui, et al.
Pubblicazione: (2024)

Relatron: Automating Relational Machine Learning over Relational Databases
di: Chen, Zhikai, et al.
Pubblicazione: (2026)

How Expressive are Knowledge Graph Foundation Models?
di: Huang, Xingyue, et al.
Pubblicazione: (2025)

TRIX: A More Expressive Model for Zero-shot Domain Transfer in Knowledge Graphs
di: Zhang, Yucheng, et al.
Pubblicazione: (2025)

LLaGA: Large Language and Graph Assistant
di: Chen, Runjin, et al.
Pubblicazione: (2024)

HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphs
di: Huang, Xingyue, et al.
Pubblicazione: (2025)

One Model, Any Conjunctive Query: Graph Neural Networks for Answering Queries over Incomplete Knowledge Graphs
di: Olejniczak, Krzysztof, et al.
Pubblicazione: (2024)

Masked Graph Autoencoder with Non-discrete Bandwidths
di: Zhao, Ziwen, et al.
Pubblicazione: (2024)

Are Expressive Encoders Necessary for Discrete Graph Generation?
di: Revolinsky, Jay, et al.
Pubblicazione: (2026)

AutoG: Towards automatic graph construction from tabular data
di: Chen, Zhikai, et al.
Pubblicazione: (2025)

Towards Better Benchmark Datasets for Inductive Knowledge Graph Completion
di: Shomer, Harry, et al.
Pubblicazione: (2024)

Graph-level Representation Learning with Joint-Embedding Predictive Architectures
di: Skenderi, Geri, et al.
Pubblicazione: (2023)

Boosting Graph Foundation Model from Structural Perspective
di: Cheng, Yao, et al.
Pubblicazione: (2024)

Toward a Graph Foundation Model: Pre-Training Transformers With Random Walks
di: Tang, Ziyuan, et al.
Pubblicazione: (2025)

PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming
di: Li, Bingheng, et al.
Pubblicazione: (2024)

Attending to Graph Transformers
di: Müller, Luis, et al.
Pubblicazione: (2023)

Mixture of Link Predictors on Graphs
di: Ma, Li, et al.
Pubblicazione: (2024)

Retrieval-Augmented Generation with Graphs (GraphRAG)
di: Han, Haoyu, et al.
Pubblicazione: (2024)

Heuristic Methods are Good Teachers to Distill MLPs for Graph Link Prediction
di: Qin, Zongyue, et al.
Pubblicazione: (2025)

Node-wise Filtering in Graph Neural Networks: A Mixture of Experts Approach
di: Han, Haoyu, et al.
Pubblicazione: (2024)

Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models
di: Zhou, Zhanke, et al.
Pubblicazione: (2025)

Towards Graph Foundation Models: A Transferability Perspective
di: Wang, Yuxiang, et al.
Pubblicazione: (2025)

Mini-batch Estimation for Deep Cox Models: Statistical Foundations and Practical Guidance
di: Zeng, Lang, et al.
Pubblicazione: (2024)

Overcoming Long-Context Limitations of State-Space Models via Context-Dependent Sparse Attention
di: Zhan, Zhihao, et al.
Pubblicazione: (2025)

Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling
di: Huang, Xingyue, et al.
Pubblicazione: (2026)