Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression. - Zhaohui Zheng 003; Ping Wang 072; Wei Liu 005; Jinze Li; Rongguang Ye; Dongwei Ren (AAAI, 2020)

A Natural Language Instruction Disambiguation Method for Robot Grasping. - Rongguang Ye; Qingchuan Xu; Jie Liu 065; Yang Hong; Chengfeng Sun; Wenzheng Chi; Lining Sun (ROBIO, 2021)

Localization Distillation for Object Detection. - Zhaohui Zheng 003; Rongguang Ye; Ping Wang 072; Jun Wang; Dongwei Ren; Wangmeng Zuo (CoRR, 2021)

Localization Distillation for Dense Object Detection. - Zhaohui Zheng 003; Rongguang Ye; Ping Wang 072; Dongwei Ren; Wangmeng Zuo; Qibin Hou; Ming-Ming Cheng (CVPR, 2022)

SIA-Unet: A Unet with Sequence Information for Gastrointestinal Tract Segmentation. - Rongguang Ye; Ranmin Wang; Yantong Guo; Lei Chen (PRICAI (1), 2022)

A Generative Adversarial Network Based Motion Planning Framework for Mobile Robots in Dynamic Human-Robot Integration Environments. - Yuqi Kong; Yao Wang; Yang Hong; Rongguang Ye; Wenzheng Chi; Lining Sun (ICSR (1), 2022)

Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation. - Zhaohui Zheng 003; Ping Wang 072; Dongwei Ren; Wei Liu 005; Rongguang Ye; Qinghua Hu; Wangmeng Zuo (IEEE Trans. Cybern., 2022)

LiCAM: Long-Tailed Instance Segmentation with Real-Time Classification Accuracy Monitoring. - Rongguang Ye; Yantong Guo; Xian Shuai; Rongye Ye; Siyang Jiang; Hui Jiang (J. Circuits Syst. Comput., 2023)

Localization Distillation for Object Detection. - Zhaohui Zheng 003; Rongguang Ye; Qibin Hou; Dongwei Ren; Ping Wang 072; Wangmeng Zuo; Ming-Ming Cheng (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Evolutionary Preference Sampling for Pareto Set Learning. - Rongguang Ye; Longcan Chen; Jinyuan Zhang; Hisao Ishibuchi (GECCO, 2024)

Collaborative Pareto Set Learning in Multiple Multi-Objective Optimization Problems. - Chikai Shang; Rongguang Ye; Jiaqi Jiang; Fangqing Gu (IJCNN, 2024)

Data-Driven Preference Sampling for Pareto Front Learning. - Rongguang Ye; Lei Chen 007; Weiduo Liao; Jinyuan Zhang; Hisao Ishibuchi (IJCNN, 2024)

A Variable-Length Fuzzy Set Representation for Learning Fuzzy-Classifier Systems. - Hiroki Shiraishi; Rongguang Ye; Hisao Ishibuchi; Masaya Nakata (PPSN (3), 2024)

An Unbounded Archive-Based Inverse Model in Evolutionary Multi-objective Optimization. - Rongguang Ye; Longcan Chen; Jinyuan Zhang; Hisao Ishibuchi (PPSN (4), 2024)

Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization. - Rongguang Ye; Longcan Chen; Wei-Bin Kou; Jinyuan Zhang; Hisao Ishibuchi (SMC, 2024)

PraFFL: A Preference-Aware Scheme in Fair Federated Learning. - Rongguang Ye; Ming Tang 006 (CoRR, 2024)

pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving. - Wei-Bin Kou; Qingfeng Lin; Ming Tang 006; Sheng Xu; Rongguang Ye; Yang Leng; Shuai Wang 004; Zhenyu Chen; Guangxu Zhu; Yik-Chung Wu (CoRR, 2024)

An Adverse Weather-Immune Scheme with Unfolded Regularization and Foundation Model Knowledge Distillation for Street Scene Understanding. - Wei-Bin Kou; Guangxu Zhu; Rongguang Ye; Shuai Wang 004; Qingfeng Lin; Ming Tang 006; Yik-Chung Wu (CoRR, 2024)

One-for-All Pruning: A Universal Model for Customized Compression of Large Language Models. - Rongguang Ye; Ming Tang 006 (ACL (Findings), 2025)

PraFFL: A Preference-Aware Scheme in Fair Federated Learning. - Rongguang Ye; Wei-Bin Kou; Ming Tang 006 (KDD (1), 2025)

Enhancing Large Vision Model in Street Scene Semantic Understanding through Leveraging Posterior Optimization Trajectory. - Wei-Bin Kou; Qingfeng Lin; Ming Tang 006; Shuai Wang 004; Rongguang Ye; Guangxu Zhu; Yik-Chung Wu (CoRR, 2025)

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator. - Wei-Bin Kou; Guangxu Zhu; Rongguang Ye; Shuai Wang 004; Ming Tang 006; Yik-Chung Wu (CoRR, 2025)

Learning Heterogeneous Performance-Fairness Trade-offs in Federated Learning. - Rongguang Ye; Ming Tang 006 (CoRR, 2025)

Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving. - Wei-Bin Kou; Qingfeng Lin; Ming Tang 006; Rongguang Ye; Shuai Wang 004; Guangxu Zhu; Yik-Chung Wu (IEEE Trans. Intell. Transp. Syst., 2025)

Adverse Weather-Independent Framework Towards Autonomous Driving Perception through Temporal Correlation and Unfolded Regularization. - Wei-Bin Kou; Guangxu Zhu; Rongguang Ye; Jingreng Lei; Shuai Wang 004; Qingfeng Lin; Ming Tang 006; Yik-Chung Wu (CoRR, 2025)