Xunkai Li
Orcid: 0000-0002-1230-7603
According to our database1,
Xunkai Li authored at least 78 papers
between 2020 and 2026.
Collaborative distances:
Collaborative distances:
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Bibliography
2026
IEEE Trans. Knowl. Data Eng., March, 2026
TMTE: Effective Multimodal Graph Learning with Task-aware Modality and Topology Co-evolution.
CoRR, March, 2026
TFPS: A Temporal Filtration-enhanced Positive Sample Set Construction Method for Implicit Collaborative Filtering.
CoRR, February, 2026
A Topology-Aware Positive Sample Set Construction and Feature Optimization Method in Implicit Collaborative Filtering.
CoRR, February, 2026
CoRR, February, 2026
A Simple yet Effective Negative Sampling Plugin for Constructing Positive Sample Pairs in Implicit Collaborative Filtering.
CoRR, February, 2026
CoRR, February, 2026
Toward Effective Multimodal Graph Foundation Model: A Divide-and-Conquer Based Approach.
CoRR, February, 2026
DOGMA: Weaving Structural Information into Data-centric Single-cell Transcriptomics Analysis.
CoRR, February, 2026
CoRR, January, 2026
CoRR, January, 2026
CoRR, January, 2026
CoRR, January, 2026
Rethinking Federated Graph Foundation Models: A Graph-Language Alignment-based Approach.
CoRR, January, 2026
DANCE: Dynamic, Available, Neighbor-gated Condensation for Federated Text-Attributed Graphs.
CoRR, January, 2026
CoRR, January, 2026
Towards effective few-shot OOD detection for text-attributed graphs via topology-Text consensus modeling.
Knowl. Based Syst., 2026
FedASU: Attention-guided sensitivity unlearning framework for multi-scenario federated graph unlearning.
Expert Syst. Appl., 2026
Unveiling the Vulnerability of Graph-LLMs: An Interpretable Multi-Dimensional Adversarial Attack on TAGs.
Proceedings of the ACM Web Conference 2026, 2026
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026
2025
CoRR, October, 2025
CoRR, October, 2025
When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach.
CoRR, October, 2025
FedBook: A Unified Federated Graph Foundation Codebook with Intra-domain and Inter-domain Knowledge Modeling.
CoRR, October, 2025
Two Facets of the Same Optimization Coin: Model Degradation and Representation Collapse in Graph Foundation Models.
CoRR, September, 2025
DFed-SST: Building Semantic- and Structure-aware Topologies for Decentralized Federated Graph Learning.
CoRR, August, 2025
CoRR, July, 2025
FedSA-GCL: A Semi-Asynchronous Federated Graph Learning Framework with Personalized Aggregation and Cluster-Aware Broadcasting.
CoRR, July, 2025
When LLMs meet open-world graph learning: a new perspective for unlabeled data uncertainty.
CoRR, May, 2025
Towards Effective Federated Graph Foundation Model via Mitigating Knowledge Entanglement.
CoRR, May, 2025
Rethinking Graph Out-Of-Distribution Generalization: A Learnable Random Walk Perspective.
CoRR, May, 2025
FedC4: Graph Condensation Meets Client-Client Collaboration for Efficient and Private Federated Graph Learning.
CoRR, April, 2025
CoRR, April, 2025
CoRR, April, 2025
CoRR, April, 2025
Proc. VLDB Endow., January, 2025
Toward Model-centric Heterogeneous Federated Graph Learning: A Knowledge-driven Approach.
CoRR, January, 2025
CoRR, January, 2025
FedPPD: Towards effective subgraph federated learning via pseudo prototype distillation.
Neural Networks, 2025
Toward Effective Digraph Representation Learning: A Magnetic Adaptive Propagation based Approach.
Proceedings of the ACM on Web Conference 2025, 2025
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025
Proceedings of the Forty-second International Conference on Machine Learning, 2025
Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025
Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025
2024
Proc. VLDB Endow., September, 2024
LightDiC: A Simple yet Effective Approach for Large-scale Digraph Representation Learning.
Proc. VLDB Endow., March, 2024
Graph Learning in the Era of LLMs: A Survey from the Perspective of Data, Models, and Tasks.
CoRR, 2024
CoRR, 2024
CoRR, 2024
Proceedings of the ACM on Web Conference 2024, 2024
FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024
Breaking the Entanglement of Homophily and Heterophily in Semi-supervised Node Classification.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024
AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024
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.
Neural Networks, July, 2023
IEEE Trans. Knowl. Data Eng., March, 2023
Proc. VLDB Endow., 2023
Effective hybrid graph and hypergraph convolution network for collaborative filtering.
Neural Comput. Appl., 2023
2022
Knowl. Inf. Syst., 2022
Handling information loss of graph convolutional networks in collaborative filtering.
Inf. Syst., 2022
Siamese Network Based Multiscale Self-Supervised Heterogeneous Graph Representation Learning.
IEEE Access, 2022
2021
A Simple Graph Convolutional Network With Abundant Interaction for Collaborative Filtering.
IEEE Access, 2021
2020