Xunkai Li

Orcid: 0000-0002-1230-7603

According to our database¹, Xunkai Li authored at least 48 papers between 2020 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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On csauthors.net:

Bibliography

2025

DFed-SST: Building Semantic- and Structure-aware Topologies for Decentralized Federated Graph Learning.

[BibT_eX]

[DOI]

CoRR, August, 2025

Federated Graph Unlearning.

[BibT_eX]

[DOI]

CoRR, August, 2025

HIAL: A New Paradigm for Hypergraph Active Learning via Influence Maximization.

[BibT_eX]

[DOI]

CoRR, July, 2025

FedSA-GCL: A Semi-Asynchronous Federated Graph Learning Framework with Personalized Aggregation and Cluster-Aware Broadcasting.

[BibT_eX]

[DOI]

CoRR, July, 2025

A Comprehensive Data-centric Overview of Federated Graph Learning.

[BibT_eX]

[DOI]

CoRR, July, 2025

Acceleration Algorithms in GNNs: A Survey.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., June, 2025

When LLMs meet open-world graph learning: a new perspective for unlabeled data uncertainty.

[BibT_eX]

[DOI]

CoRR, May, 2025

Towards Effective Federated Graph Foundation Model via Mitigating Knowledge Entanglement.

[BibT_eX]

[DOI]

CoRR, May, 2025

Rethinking Graph Out-Of-Distribution Generalization: A Learnable Random Walk Perspective.

[BibT_eX]

[DOI]

CoRR, May, 2025

Rethinking Federated Graph Learning: A Data Condensation Perspective.

[BibT_eX]

[DOI]

CoRR, May, 2025

Toward Data-centric Directed Graph Learning: An Entropy-driven Approach.

[BibT_eX]

[DOI]

CoRR, May, 2025

FedC4: Graph Condensation Meets Client-Client Collaboration for Efficient and Private Federated Graph Learning.

[BibT_eX]

[DOI]

CoRR, April, 2025

Towards Unbiased Federated Graph Learning: Label and Topology Perspectives.

[BibT_eX]

[DOI]

CoRR, April, 2025

Federated Prototype Graph Learning.

[BibT_eX]

[DOI]

CoRR, April, 2025

Toward General and Robust LLM-enhanced Text-attributed Graph Learning.

[BibT_eX]

[DOI]

CoRR, April, 2025

GraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments.

[BibT_eX]

[DOI]

CoRR, April, 2025

Rethinking Graph Structure Learning in the Era of LLMs.

[BibT_eX]

[DOI]

CoRR, March, 2025

OpenFGL: A Comprehensive Benchmark for Federated Graph Learning.

[BibT_eX]

[DOI]

Proc. VLDB Endow., January, 2025

ScaDyG:A New Paradigm for Large-scale Dynamic Graph Learning.

[BibT_eX]

[DOI]

CoRR, January, 2025

Toward Model-centric Heterogeneous Federated Graph Learning: A Knowledge-driven Approach.

[BibT_eX]

[DOI]

CoRR, January, 2025

Toward Scalable Graph Unlearning: A Node Influence Maximization based Approach.

[BibT_eX]

[DOI]

CoRR, January, 2025

OpenGU: A Comprehensive Benchmark for Graph Unlearning.

[BibT_eX]

[DOI]

CoRR, January, 2025

FedPPD: Towards effective subgraph federated learning via pseudo prototype distillation.

[BibT_eX]

[DOI]

Neural Networks, 2025

Toward Effective Digraph Representation Learning: A Magnetic Adaptive Propagation based Approach.

[BibT_eX]

[DOI]

Proceedings of the ACM on Web Conference 2025, 2025

2024

Topology-preserving Graph Coarsening: An Elementary Collapse-based Approach.

[BibT_eX]

[DOI]

Proc. VLDB Endow., September, 2024

LightDiC: A Simple yet Effective Approach for Large-scale Digraph Representation Learning.

[BibT_eX]

[DOI]

Proc. VLDB Endow., March, 2024

Graph Learning in the Era of LLMs: A Survey from the Perspective of Data, Models, and Tasks.

[BibT_eX]

[DOI]

CoRR, 2024

Towards Data-centric Machine Learning on Directed Graphs: a Survey.

[BibT_eX]

[DOI]

CoRR, 2024

Federated Continual Graph Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Toward Personalized Federated Node Classification in One-shot Communication.

[BibT_eX]

[DOI]

CoRR, 2024

DiRW: Path-Aware Digraph Learning for Heterophily.

[BibT_eX]

[DOI]

CoRR, 2024

OpenFGL: A Comprehensive Benchmarks for Federated Graph Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Internal Consistency and Self-Feedback in Large Language Models: A Survey.

[BibT_eX]

[DOI]

CoRR, 2024

Acceleration Algorithms in GNNs: A Survey.

[BibT_eX]

[DOI]

CoRR, 2024

Rethinking Node-wise Propagation for Large-scale Graph Learning.

[BibT_eX]

[DOI]

Proceedings of the ACM on Web Conference 2024, 2024

FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Breaking the Entanglement of Homophily and Heterophily in Semi-supervised Node Classification.

[BibT_eX]

[DOI]

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity.

[BibT_eX]

[DOI]

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Towards Effective and General Graph Unlearning via Mutual Evolution.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

LoyalDE: Improving the performance of Graph Neural Networks with loyal node discovery and emphasis.

[BibT_eX]

[DOI]

Neural Networks, July, 2023

Adaptive Hypergraph Auto-Encoder for Relational Data Clustering.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., March, 2023

FedGTA: Topology-aware Averaging for Federated Graph Learning.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2023

Effective hybrid graph and hypergraph convolution network for collaborative filtering.

[BibT_eX]

[DOI]

Neural Comput. Appl., 2023

2022

Graph relation embedding network for click-through rate prediction.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2022

Handling information loss of graph convolutional networks in collaborative filtering.

[BibT_eX]

[DOI]

Inf. Syst., 2022

Siamese Network Based Multiscale Self-Supervised Heterogeneous Graph Representation Learning.

[BibT_eX]

[DOI]

IEEE Access, 2022

2021

A Simple Graph Convolutional Network With Abundant Interaction for Collaborative Filtering.

[BibT_eX]

[DOI]

IEEE Access, 2021

2020

A Deep Graph Structured Clustering Network.

[BibT_eX]

[DOI]

IEEE Access, 2020

Xunkai Li

Timeline

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Links

On csauthors.net:

Bibliography

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