:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Yuan, Zhongzheng, Guo, Lianshuai, Li, Xunkai, Wang, Wenyu, Qu, Meixia
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2605.08178
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

Federated Prototype Graph Learning
by: Wu, Zhengyu, et al.
Published: (2025)

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

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

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

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

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

ProtoGCD: Unified and Unbiased Prototype Learning for Generalized Category Discovery
by: Ma, Shijie, et al.
Published: (2025)

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

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

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

Learning Part Knowledge to Facilitate Category Understanding for Fine-Grained Generalized Category Discovery
by: Wang, Enguang, et al.
Published: (2025)

Generalized Category Discovery with Large Language Models in the Loop
by: An, Wenbin, et al.
Published: (2023)

Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
by: Mao, Wenyu, et al.
Published: (2024)

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

The Devil Is in Gradient Entanglement: Energy-Aware Gradient Coordinator for Robust Generalized Category Discovery
by: Zheng, Haiyang, et al.
Published: (2026)

A Generic Method for Fine-grained Category Discovery in Natural Language Texts
by: Tian, Chang, et al.
Published: (2024)

DiRW: Path-Aware Digraph Learning for Heterophily
by: Su, Daohan, et al.
Published: (2024)

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

Diffusion Model-Based Data Synthesis Aided Federated Semi-Supervised Learning
by: Wang, Zhongwei, et al.
Published: (2025)

Towards Data-centric Machine Learning on Directed Graphs: a Survey
by: Sun, Henan, et al.
Published: (2024)

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

Graph Learning in the Era of LLMs: A Survey from the Perspective of Data, Models, and Tasks
by: Li, Xunkai, et al.
Published: (2024)

Toward Data-centric Directed Graph Learning: An Entropy-driven Approach
by: Li, Xunkai, et al.
Published: (2025)

Proactive Depot Discovery: A Generative Framework for Flexible Location-Routing
by: Qu, Site, et al.
Published: (2025)

AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity
by: Li, Xunkai, et al.
Published: (2024)

Hypergraph Attacks via Injecting Homogeneous Nodes into Elite Hyperedges
by: He, Meixia, et al.
Published: (2024)

LLM4ED: Large Language Models for Automatic Equation Discovery
by: Du, Mengge, et al.
Published: (2024)

AnalogFed: Federated Discovery of Analog Circuit Topologies with Generative AI
by: Li, Qiufeng, et al.
Published: (2025)

Exploring Federated Pruning for Large Language Models
by: Guo, Pengxin, et al.
Published: (2025)

FedCCRL: Federated Domain Generalization with Cross-Client Representation Learning
by: Wang, Xinpeng, et al.
Published: (2024)

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

Federated Graph Learning for Cross-Domain Recommendation
by: Yang, Ziqi, et al.
Published: (2024)

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning?
by: Ding, Wenjun, et al.
Published: (2024)

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

SpreadFGL: Edge-Client Collaborative Federated Graph Learning with Adaptive Neighbor Generation
by: Zhong, Luying, et al.
Published: (2024)

Generalized Category Discovery under Domain Shifts: From Vision to Vision-Language Models
by: Wang, Hongjun, et al.
Published: (2026)

SpectralGCD: Spectral Concept Selection and Cross-modal Representation Learning for Generalized Category Discovery
by: Caselli, Lorenzo, et al.
Published: (2026)

Mixed-Precision Federated Learning via Multi-Precision Over-The-Air Aggregation
by: Yuan, Jinsheng, et al.
Published: (2024)