Relation-Aware Graph Foundation Model
Fuente:
arXiv
Saved in:
| Main Authors: | Yu, Jianxiang, Zhu, Jiapeng, Qian, Hao, Liu, Ziqi, Zhang, Zhiqiang, Li, Xiang |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt Tuning
by: Zhu, Jiapeng, et al.
Published: (2024)
by: Zhu, Jiapeng, et al.
Published: (2024)
Hierarchical Vector Quantized Graph Autoencoder with Annealing-Based Code Selection
by: Zeng, Long, et al.
Published: (2025)
by: Zeng, Long, et al.
Published: (2025)
Boosting Graph Foundation Model from Structural Perspective
by: Cheng, Yao, et al.
Published: (2024)
by: Cheng, Yao, et al.
Published: (2024)
Class-Balanced and Reinforced Active Learning on Graphs
by: Yu, Chengcheng, et al.
Published: (2024)
by: Yu, Chengcheng, et al.
Published: (2024)
MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction
by: Qian, Hao, et al.
Published: (2024)
by: Qian, Hao, et al.
Published: (2024)
Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Adaptively Weighted Negative Samples
by: Yu, Jianxiang, et al.
Published: (2022)
by: Yu, Jianxiang, et al.
Published: (2022)
Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed Graphs
by: Yu, Jianxiang, et al.
Published: (2023)
by: Yu, Jianxiang, et al.
Published: (2023)
Uncertainty-Aware Foundation Models for Clinical Data
by: Zhou, Qian, et al.
Published: (2026)
by: Zhou, Qian, et al.
Published: (2026)
Improving Graph Out-of-distribution Generalization Beyond Causality
by: Xu, Can, et al.
Published: (2024)
by: Xu, Can, et al.
Published: (2024)
Human Cognition Inspired RAG with Knowledge Graph for Complex Problem Solving
by: Cheng, Yao, et al.
Published: (2025)
by: Cheng, Yao, et al.
Published: (2025)
MergeMix: Optimizing Mid-Training Data Mixtures via Learnable Model Merging
by: Wang, Jiapeng, et al.
Published: (2026)
by: Wang, Jiapeng, et al.
Published: (2026)
Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural Networks
by: Gong, Chenghua, et al.
Published: (2023)
by: Gong, Chenghua, et al.
Published: (2023)
DMAGT: Unveiling miRNA-Drug Associations by Integrating SMILES and RNA Sequence Structures through Graph Transformer Models
by: Zhang, Ziqi
Published: (2025)
by: Zhang, Ziqi
Published: (2025)
Variational Graph Autoencoder for Heterogeneous Information Networks with Missing and Inaccurate Attributes
by: Zhao, Yige, et al.
Published: (2023)
by: Zhao, Yige, et al.
Published: (2023)
Enhancing LLM Tool Use with High-quality Instruction Data from Knowledge Graph
by: Wang, Jingwei, et al.
Published: (2025)
by: Wang, Jingwei, et al.
Published: (2025)
Out-of-Distribution Generalization in Graph Foundation Models
by: Li, Haoyang, et al.
Published: (2026)
by: Li, Haoyang, et al.
Published: (2026)
Graph Foundation Models: Concepts, Opportunities and Challenges
by: Liu, Jiawei, et al.
Published: (2023)
by: Liu, Jiawei, et al.
Published: (2023)
RiemannGFM: Learning a Graph Foundation Model from Riemannian Geometry
by: Sun, Li, et al.
Published: (2025)
by: Sun, Li, et al.
Published: (2025)
Deeper with Riemannian Geometry: Overcoming Oversmoothing and Oversquashing for Graph Foundation Models
by: Sun, Li, et al.
Published: (2025)
by: Sun, Li, et al.
Published: (2025)
Retrieval-Augmented Foundation Models for Matched Molecular Pair Transformations to Recapitulate Medicinal Chemistry Intuition
by: Pan, Bo, et al.
Published: (2026)
by: Pan, Bo, et al.
Published: (2026)
Learning Graph Foundation Models on Riemannian Graph-of-Graphs
by: Liu, Haokun, et al.
Published: (2026)
by: Liu, Haokun, et al.
Published: (2026)
GNNVerifier: Graph-based Verifier for LLM Task Planning
by: Hao, Yu, et al.
Published: (2026)
by: Hao, Yu, et al.
Published: (2026)
Rethinking Federated Graph Foundation Models: A Graph-Language Alignment-based Approach
by: Zhu, Yinlin, et al.
Published: (2026)
by: Zhu, Yinlin, et al.
Published: (2026)
RegionGCN: Spatial-Heterogeneity-Aware Graph Convolutional Networks
by: Guo, Hao, et al.
Published: (2025)
by: Guo, Hao, et al.
Published: (2025)
GraphFM: A Comprehensive Benchmark for Graph Foundation Model
by: Xu, Yuhao, et al.
Published: (2024)
by: Xu, Yuhao, et al.
Published: (2024)
Enhancing Missing Data Imputation through Combined Bipartite Graph and Complete Directed Graph
by: Zhang, Zhaoyang, et al.
Published: (2024)
by: Zhang, Zhaoyang, et al.
Published: (2024)
Priority-Aware Shapley Value
by: Lee, Kiljae, et al.
Published: (2026)
by: Lee, Kiljae, et al.
Published: (2026)
Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data
by: Hu, Binbin, et al.
Published: (2024)
by: Hu, Binbin, et al.
Published: (2024)
GLIP-OOD: Zero-Shot Graph OOD Detection with Graph Foundation Model
by: Xu, Haoyan, et al.
Published: (2025)
by: Xu, Haoyan, et al.
Published: (2025)
Text-Free Multi-domain Graph Pre-training: Toward Graph Foundation Models
by: Yu, Xingtong, et al.
Published: (2024)
by: Yu, Xingtong, et al.
Published: (2024)
Text Detoxification: Data Efficiency, Semantic Preservation and Model Generalization
by: Yu, Jing, et al.
Published: (2025)
by: Yu, Jing, et al.
Published: (2025)
Multi-Domain Riemannian Graph Gluing for Building Graph Foundation Models
by: Sun, Li, et al.
Published: (2026)
by: Sun, Li, et al.
Published: (2026)
WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training
by: Tian, Changxin, et al.
Published: (2025)
by: Tian, Changxin, et al.
Published: (2025)
FFHFlow: Diverse and Uncertainty-Aware Dexterous Grasp Generation via Flow Variational Inference
by: Feng, Qian, et al.
Published: (2024)
by: Feng, Qian, et al.
Published: (2024)
Sampling-guided Heterogeneous Graph Neural Network with Temporal Smoothing for Scalable Longitudinal Data Imputation
by: Zhang, Zhaoyang, et al.
Published: (2024)
by: Zhang, Zhaoyang, et al.
Published: (2024)
Griffin: Towards a Graph-Centric Relational Database Foundation Model
by: Wang, Yanbo, et al.
Published: (2025)
by: Wang, Yanbo, et al.
Published: (2025)
GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning
by: Yuan, Haonan, et al.
Published: (2025)
by: Yuan, Haonan, et al.
Published: (2025)
Navigating Spatio-Temporal Heterogeneity: A Graph Transformer Approach for Traffic Forecasting
by: Zhou, Jianxiang, et al.
Published: (2024)
by: Zhou, Jianxiang, et al.
Published: (2024)
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
by: Chen, Zhikai, et al.
Published: (2024)
by: Chen, Zhikai, et al.
Published: (2024)
A Systematic Study of Model Extraction Attacks on Graph Foundation Models
by: Xu, Haoyan, et al.
Published: (2025)
by: Xu, Haoyan, et al.
Published: (2025)
Similar Items
-
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt Tuning
by: Zhu, Jiapeng, et al.
Published: (2024) -
Hierarchical Vector Quantized Graph Autoencoder with Annealing-Based Code Selection
by: Zeng, Long, et al.
Published: (2025) -
Boosting Graph Foundation Model from Structural Perspective
by: Cheng, Yao, et al.
Published: (2024) -
Class-Balanced and Reinforced Active Learning on Graphs
by: Yu, Chengcheng, et al.
Published: (2024) -
MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction
by: Qian, Hao, et al.
Published: (2024)