Imagen de Portada

Rethinking Federated Graph Foundation Models: A Graph-Language Alignment-based Approach

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhu, Yinlin, Wu, Di, Zhang, Xianzhi, Ai, Yuming, Li, Xunkai, Hu, Miao, Quan, Guocong
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Both Topology and Text Matter: Revisiting LLM-guided Out-of-Distribution Detection on Text-attributed Graphs
por: Zhu, Yinlin, et al.
Publicado: (2026)

Towards Effective Federated Graph Foundation Model via Mitigating Knowledge Entanglement
por: Zhu, Yinlin, et al.
Publicado: (2025)

Rethinking Federated Graph Learning: A Data Condensation Perspective
por: Zhang, Hao, et al.
Publicado: (2025)

Rethinking Client-oriented Federated Graph Learning
por: Chen, Zekai, et al.
Publicado: (2025)

Federated Graph Unlearning
por: Ai, Yuming, et al.
Publicado: (2025)

Adapter-Augmented Bandits for Online Multi-Constrained Multi-Modal Inference Scheduling
por: Zhang, Xianzhi, et al.
Publicado: (2026)

Federated Continual Graph Learning
por: Zhu, Yinlin, et al.
Publicado: (2024)

TMTE: Effective Multimodal Graph Learning with Task-aware Modality and Topology Co-evolution
por: Zhu, Yinlin, et al.
Publicado: (2026)

FedBook: A Unified Federated Graph Foundation Codebook with Intra-domain and Inter-domain Knowledge Modeling
por: Wu, Zhengyu, et al.
Publicado: (2025)

MM-OpenFGL: A Comprehensive Benchmark for Multimodal Federated Graph Learning
por: Li, Xunkai, et al.
Publicado: (2026)

Federated Prototype Graph Learning
por: Wu, Zhengyu, et al.
Publicado: (2025)

A Comprehensive Data-centric Overview of Federated Graph Learning
por: Wu, Zhengyu, et al.
Publicado: (2025)

FedGTA: Topology-aware Averaging for Federated Graph Learning
por: Li, Xunkai, et al.
Publicado: (2024)

FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning
por: Zhu, Yinlin, et al.
Publicado: (2024)

DFed-SST: Building Semantic- and Structure-aware Topologies for Decentralized Federated Graph Learning
por: Guo, Lianshuai, et al.
Publicado: (2025)

GOMA: Toward Structure-Driven Multimodal Alignment from a Graph Signal Smoothing Perspective
por: Wang, Xu, et al.
Publicado: (2026)

FedSA-GCL: A Semi-Asynchronous Federated Graph Learning Framework with Personalized Aggregation and Cluster-Aware Broadcasting
por: Yuan, Zhongzheng, et al.
Publicado: (2025)

Knowledge-Driven Federated Graph Learning on Model Heterogeneity
por: Wu, Zhengyu, et al.
Publicado: (2025)

Rethinking Multimodal Point Cloud Completion: A Completion-by-Correction Perspective
por: Luo, Wang, et al.
Publicado: (2025)

Towards Unbiased Federated Graph Learning: Label and Topology Perspectives
por: Wu, Zhengyu, et al.
Publicado: (2025)

OpenFGL: A Comprehensive Benchmark for Federated Graph Learning
por: Li, Xunkai, et al.
Publicado: (2024)

OpenGU: A Comprehensive Benchmark for Graph Unlearning
por: Fan, Bowen, et al.
Publicado: (2025)

Rethinking Graph Out-Of-Distribution Generalization: A Learnable Random Walk Perspective
por: Sun, Henan, et al.
Publicado: (2025)

Toward Effective Multimodal Graph Foundation Model: A Divide-and-Conquer Based Approach
por: Liu, Sicheng, et al.
Publicado: (2026)

Personalized One-shot Federated Graph Learning for Heterogeneous Clients
por: Yan, Guochen, et al.
Publicado: (2024)

STAGE: Tackling Semantic Drift in Multimodal Federated Graph Learning
por: Chen, Zekai, et al.
Publicado: (2026)

Generalized Category Discovery in Federated Graph Learning
por: Yuan, Zhongzheng, et al.
Publicado: (2026)

Rethinking Node-wise Propagation for Large-scale Graph Learning
por: Li, Xunkai, et al.
Publicado: (2024)

Two Facets of the Same Optimization Coin: Model Degradation and Representation Collapse in Graph Foundation Models
por: Li, Xunkai, et al.
Publicado: (2025)

Unlocking Graph Structure Learning with Tree-Guided Large Language Models
por: Zhang, Zhihan, et al.
Publicado: (2025)

Rethinking Graph Masked Autoencoders through Alignment and Uniformity
por: Wang, Liang, et al.
Publicado: (2024)

Rethinking Feature Alignment in Generalist Graph Anomaly Detection: A Relational Fingerprint-based Approach
por: Liu, Yujing, et al.
Publicado: (2026)

Toward Scalable Graph Unlearning: A Node Influence Maximization based Approach
por: Li, Xunkai, et al.
Publicado: (2025)

State Space Models over Directed Graphs
por: She, Junzhi, et al.
Publicado: (2025)

RoleMAG: Learning Neighbor Roles in Multimodal Graphs
por: Zuo, Yilong, et al.
Publicado: (2026)

BoostFGL: Boosting Fairness in Federated Graph Learning
por: Chen, Zekai, et al.
Publicado: (2026)

GraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments
por: Du, Enjun, et al.
Publicado: (2025)

Towards Robust Federated Multimodal Graph Learning under Modality Heterogeneity
por: Zhang, Sirui, et al.
Publicado: (2026)

Relation-Aware Graph Foundation Model
por: Yu, Jianxiang, et al.
Publicado: (2025)

DANCE: Dynamic, Available, Neighbor-gated Condensation for Federated Text-Attributed Graphs
por: Chen, Zekai, et al.
Publicado: (2026)