GitFL: Uncertainty-Aware Real-Time Asynchronous Federated Learning Using Version Control. - Ming Hu 003; Zeke Xia; Dengke Yan; Zhihao Yue; Jun Xia 003; Yihao Huang 001; Yang Liu 003; Mingsong Chen 001 (RTSS, 2023)

Brief Industry Paper: Towards Efficient Task Scheduling for AUTOSAR using Parallel Pruning. - Yanxing Yang; Nan Zhang 019; Dengke Yan; Xian Wei; Junlong Zhou; Hong Liu; Mingsong Chen 001 (RTSS, 2023)

Have Your Cake and Eat It Too: Toward Efficient and Accurate Split Federated Learning. - Dengke Yan; Ming Hu 003; Zeke Xia; Yanxin Yang; Jun Xia 003; Xiaofei Xie; Mingsong Chen 001 (CoRR, 2023)

SampDetox: Black-box Backdoor Defense via Perturbation-based Sample Detoxification. - Yanxin Yang; Chentao Jia; Dengke Yan; Ming Hu 003; Tianlin Li; Xiaofei Xie; Xian Wei; Mingsong Chen 001 (NeurIPS, 2024)

KoReA-SFL: Knowledge Replay-based Split Federated Learning Against Catastrophic Forgetting. - Zeke Xia; Ming Hu 003; Dengke Yan; Ruixuan Liu; Anran Li 001; Xiaofei Xie; Mingsong Chen 001 (CoRR, 2024)

CaBaFL: Asynchronous Federated Learning via Hierarchical Cache and Feature Balance. - Zeke Xia; Ming Hu 003; Dengke Yan; Xiaofei Xie; Tianlin Li; Anran Li 001; Junlong Zhou; Mingsong Chen 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

MultiSFL: Towards Accurate Split Federated Learning via Multi-Model Aggregation and Knowledge Replay. - Zeke Xia; Ming Hu 003; Dengke Yan; Ruixuan Liu; Anran Li 001; Xiaofei Xie; Mingsong Chen 001 (AAAI, 2025)