Yinlin Zhu

According to our database, Yinlin Zhu authored at least 30 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

GOMA: Toward Structure-Driven Multimodal Alignment from a Graph Signal Smoothing Perspective.

Xu Wang, Xunkai Li, Yinlin Zhu, Rong-Hua Li, Guoren Wang

CoRR, May, 2026

CAMPA: Efficient and Aligned Multimodal Graph Learning via Decoupled Propagation and Aggregation.

Daohan Su, Hao Liu, Xunkai Li, Yinlin Zhu, Xiong Yongfu, Yi Liu, Hongchao Qin, Rong-Hua Li, Guoren Wang

CoRR, May, 2026

TMTE: Effective Multimodal Graph Learning with Task-aware Modality and Topology Co-evolution.

Yinlin Zhu, Xunkai Li, Di Wu, Wang Luo, Miao Hu, Guocong Quan

CoRR, March, 2026

Adapter-Augmented Bandits for Online Multi-Constrained Multi-Modal Inference Scheduling.

Xianzhi Zhang, Yue Xu, Yinlin Zhu, Di Wu, Yipeng Zhou, Miao Hu, Guocong Quan

CoRR, March, 2026

Both Topology and Text Matter: Revisiting LLM-guided Out-of-Distribution Detection on Text-attributed Graphs.

Yinlin Zhu, Di Wu, Xu Wang, Guocong Quan, Miao Hu

CoRR, February, 2026

MM-OpenFGL: A Comprehensive Benchmark for Multimodal Federated Graph Learning.

Xunkai Li, Yuming Ai, Yinlin Zhu, Haodong Lu, Yi Zhang, Guohao Fu, Bowen Fan, Qiangqiang Dai, Rong-Hua Li, Guoren Wang

CoRR, January, 2026

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

Yinlin Zhu, Di Wu, Xianzhi Zhang, Yuming Ai, Xunkai Li, Miao Hu, Guocong Quan

CoRR, January, 2026

Towards effective few-shot OOD detection for text-attributed graphs via topology-Text consensus modeling.

Xu Wang, Yinlin Zhu, Xunkai Li, Meixia Qu, Wenyu Wang

Knowl. Based Syst., 2026

Rethinking Multimodal Point Cloud Completion: A Completion-by-Correction Perspective.

Wang Luo, Di Wu, Hengyuan Na, Yinlin Zhu, Miao Hu, Guocong Quan

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

PAGE: A Unified Approach for Federated Graph Unlearning.

Yuming Ai, Xunkai Li, Jiaqi Chao, Bowen Fan, Zhengyu Wu, Yinlin Zhu, Rong-Hua Li, Guoren Wang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

FedBook: A Unified Federated Graph Foundation Codebook with Intra-domain and Inter-domain Knowledge Modeling.

Zhengyu Wu, Yinlin Zhu, Xunkai Li, Ziang Qiu, Rong-Hua Li, Guoren Wang, Chenghu Zhou

CoRR, October, 2025

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

Lianshuai Guo, Zhongzheng Yuan, Xunkai Li, Yinlin Zhu, Meixia Qu, Wenyu Wang

CoRR, August, 2025

Federated Graph Unlearning.

Yuming Ai, Xunkai Li, Jiaqi Chao, Bowen Fan, Zhengyu Wu, Yinlin Zhu, Rong-Hua Li, Guoren Wang

CoRR, August, 2025

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

Zhongzheng Yuan, Lianshuai Guo, Xunkai Li, Yinlin Zhu, Wenyu Wang, Meixia Qu

CoRR, July, 2025

A Comprehensive Data-centric Overview of Federated Graph Learning.

Zhengyu Wu, Xunkai Li, Yinlin Zhu, Zekai Chen, Guochen Yan, Yanyu Yan, Hao Zhang, Yuming Ai, Xinmo Jin, Rong-Hua Li, Guoren Wang

CoRR, July, 2025

Towards Effective Federated Graph Foundation Model via Mitigating Knowledge Entanglement.

Yinlin Zhu, Xunkai Li, Jishuo Jia, Miao Hu, Di Wu, Meikang Qiu

CoRR, May, 2025

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

Zekai Chen, Xunkai Li, Yinlin Zhu, Rong-Hua Li, Guoren Wang

CoRR, April, 2025

Towards Unbiased Federated Graph Learning: Label and Topology Perspectives.

Zhengyu Wu, Boyang Pang, Xunkai Li, Yinlin Zhu, Daohan Su, Bowen Fan, Rong-Hua Li, Guoren Wang, Chenghu Zhou

CoRR, April, 2025

Federated Prototype Graph Learning.

Zhengyu Wu, Xunkai Li, Yinlin Zhu, Rong-Hua Li, Guoren Wang, Chenghu Zhou

CoRR, April, 2025

OpenFGL: A Comprehensive Benchmark for Federated Graph Learning.

Xunkai Li, Yinlin Zhu, Boyang Pang, Guochen Yan, Yeyu Yan, Zening Li, Zhengyu Wu, Wentao Zhang, Ronghua Li, Guoren Wang

Proc. VLDB Endow., January, 2025

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

Huilin Lai, Guang Zeng, Xunkai Li, Xudong Shen, Yinlin Zhu, Ye Luo, Jianwei Lu, Lei Zhu

CoRR, January, 2025

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

Qi Lin, Jishuo Jia, Yinlin Zhu, Xunkai Li, Bin Jiang, Meixia Qu

Neural Networks, 2025

Federated Continual Graph Learning.

Yinlin Zhu, Miao Hu, Di Wu

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

Rethinking Federated Graph Learning: A Data Condensation Perspective.

Hao Zhang, Xunkai Li, Yinlin Zhu, Lianglin Hu

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Rethinking Client-oriented Federated Graph Learning.

Zekai Chen, Xunkai Li, Yinlin Zhu, Rong-Hua Li, Guoren Wang

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

2024

Federated Continual Graph Learning.

Yinlin Zhu, Xunkai Li, Miao Hu, Di Wu

CoRR, 2024

OpenFGL: A Comprehensive Benchmarks for Federated Graph Learning.

Xunkai Li, Yinlin Zhu, Boyang Pang, Guochen Yan, Yeyu Yan, Zening Li, Zhengyu Wu, Wentao Zhang, Rong-Hua Li, Guoren Wang

CoRR, 2024

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

Yinlin Zhu, Xunkai Li, Zhengyu Wu, Di Wu, Miao Hu, Rong-Hua Li

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

2023

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

Haotong Wei, Yinlin Zhu, Xunkai Li, Bin Jiang

Neural Networks, July, 2023

FedGTA: Topology-aware Averaging for Federated Graph Learning.

Xunkai Li, Zhengyu Wu, Wentao Zhang, Yinlin Zhu, Ronghua Li, Guoren Wang

Proc. VLDB Endow., 2023