| 2025 | ICRA | Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator. | Wei-Bin Kou, Guangxu Zhu, Rongguang Ye, Shuai Wang, Ming Tang, Yik-Chung Wu |
| 2025 | IROS | Enhancing Large Vision Model in Street Scene Semantic Understanding through Leveraging Posterior Optimization Trajectory. | Wei-Bin Kou, Qingfeng Lin, Ming Tang, Jingreng Lei, Shuai Wang, Rongguang Ye, Guangxu Zhu, Yik-Chung Wu |
| 2025 | IROS | FedEMA: Federated Exponential Moving Averaging with Negative Entropy Regularizer in Autonomous Driving. | Wei-Bin Kou, Guangxu Zhu, Bingyang Cheng, Shuai Wang, Ming Tang, Yik-Chung Wu |
| 2025 | KDD | PraFFL: A Preference-Aware Scheme in Fair Federated Learning. | Rongguang Ye, Wei-Bin Kou, Ming Tang |
| 2024 | IROS | FedRC: A Rapid-Converged Hierarchical Federated Learning Framework in Street Scene Semantic Understanding. | Wei-Bin Kou, Qingfeng Lin, Ming Tang, Shuai Wang, Guangxu Zhu, Yik-Chung Wu |
| 2024 | SMC | Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization. | Rongguang Ye, Longcan Chen, Wei-Bin Kou, Jinyuan Zhang, Hisao Ishibuchi |
| 2023 | IROS | Communication Resources Constrained Hierarchical Federated Learning for End-to-End Autonomous Driving. | Wei-Bin Kou, Shuai Wang, Guangxu Zhu, Bin Luo, Yingxian Chen, Derrick Wing Kwan Ng, Yik-Chung Wu |