Split Federated Learning Empowered Vehicular Edge Intelligence: Adaptive Parellel Design and Future Directions. - Xianke Qiang; Zheng Chang 001; Chaoxiong Ye; Timo Hämäläinen 002; Geyong Min (CoRR, 2024)

Importance-aware data selection and resource allocation for hierarchical federated edge learning. - Xianke Qiang; Yun Hu 001; Zheng Chang 001; Timo Hämäläinen 002 (Future Gener. Comput. Syst., 2024)

GenFV: AIGC-Assisted Federated Learning for Vehicular Edge Intelligence. - Xianke Qiang; Zheng Chang 001; Adrian Kliks (EuCNC/6G Summit, 2025)

AIGC-assisted Federated Learning for Vehicular Edge Intelligence: Vehicle Selection, Resource Allocation and Model Augmentation. - Xianke Qiang; Zheng Chang 001; Geyong Min (CoRR, 2025)

AIGC-assisted Federated Learning for Edge Intelligence: Architecture Design, Research Challenges and Future Directions. - Xianke Qiang; Zheng Chang 001; Ying-Chang Liang (CoRR, 2025)

Adaptive and Parallel Split Federated Learning in Vehicular Edge Computing. - Xianke Qiang; Zheng Chang 001; Yun Hu 001; Lei Liu 031; Timo Hämäläinen 002 (IEEE Internet Things J., 2025)

Deploying Large AI Models on Resource-Limited Devices with Split Federated Learning. - Xianke Qiang; Hongda Liu; Xinran Zhang; Zheng Chang 001; Ying-Chang Liang (CoRR, 2025)

Split Federated Learning Empowered Vehicular Edge Intelligence: Concept, Adaptive Design, and Future Directions. - Xianke Qiang; Zheng Chang 001; Chaoxiong Ye; Timo Hämäläinen 002; Geyong Min (IEEE Wirel. Commun., 2025)