Learning with Free Object Segments for Long-Tailed Instance Segmentation. - Cheng Zhang 014; Tai-Yu Pan; Tianle Chen; Jike Zhong; Wenjin Fu; Wei-Lun Chao (ECCV (10), 2022)

Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data. - Cheng-Hao Tu 001; Hong-You Chen; Zheda Mai; Jike Zhong; Vardaan Pahuja; Tanya Y. Berger-Wolf; Song Gao 001; Charles V. Stewart; Yu Su 001; Wei-Lun Chao (NeurIPS, 2023)

Making Batch Normalization Great in Federated Deep Learning. - Jike Zhong; Hong-You Chen; Wei-Lun Chao (CoRR, 2023)

Federated Learning of Shareable Bases for Personalization-Friendly Image Classification. - Hong-You Chen; Jike Zhong; Mingda Zhang; Xuhui Jia; Hang Qi; Boqing Gong; Wei-Lun Chao; Li Zhang 003 (CoRR, 2023)

Vision-Language Model Fine-Tuning via Simple Parameter-Efficient Modification. - Ming Li; Jike Zhong; Chenxin Li; Liuzhuozheng Li; Nie Lin; Masashi Sugiyama (EMNLP, 2024)

EEE-Bench: A Comprehensive Multimodal Electrical And Electronics Engineering Benchmark. - Ming Li; Jike Zhong; Tianle Chen; Yuxiang Lai; Konstantinos Psounis (CVPR, 2025)

Med-R1: Reinforcement Learning for Generalizable Medical Reasoning in Vision-Language Models. - Yuxiang Lai; Jike Zhong; Ming Li; Shitian Zhao; Xiaofeng Yang (CoRR, 2025)

Think or Not Think: A Study of Explicit Thinking inRule-Based Visual Reinforcement Fine-Tuning. - Ming Li; Jike Zhong; Shitian Zhao; Yuxiang Lai; Kaipeng Zhang (CoRR, 2025)

Patient-Specific Autoregressive Models for Organ Motion Prediction in Radiotherapy. - Yuxiang Lai; Jike Zhong; Vanessa Su; Xiaofeng Yang (CoRR, 2025)