Hello, I am currently pursuing a Ph.D. in computer science at the State Key Laboratory of Internet of Things for Smart City (SKL-IOTSC), University of Macau, under the supervision of Prof. Jianbing Shen (IEEE Fellow). Concurrently, I am working under the guidance of Prof. Yu Cheng from the Chinese University of Hong Kong. I completed my master’s degree from Fudan University, supervised by Prof. Wenqiang Zhang. Throughout my academic journey, I have been fortunate to collaborate with Dr. Xiubo Geng from Microsoft, Prof. Guodong Long from the University of Technology Sydney, and Dr. Tao Shen from Oracle.

My research centers on Large Language Models, and Multimodal Models, supported by the Fundamental Research Project for Young Ph.D. students from NSFC (国家自然科学基金青年学生基础研究项目(博士生)). The overarching goal of my work is to advance machine intelligence to serve humanity. My interests are the understanding, analysis, and improvement of LLMs/MLLMs and their applications in AI Healthcare and Visual Generation. I am always open for research discussions and collaborations. If you are interested in discussing or collaborating, please feel free to contact me via email.

Selected Preprint 📝

Yucheng Zhou, Jihai Zhang, Guanjie Chen, Jianbing Shen, Yu Cheng. Less Is More: Vision Representation Compression for Efficient Video Generation with Large Language Models. (pdf).

Yucheng Zhou, Zhi Rao, Jun Wan, Jianbing Shen. Rethinking Visual Dependency in Long-Context Reasoning for Large Vision-Language Models. (pdf).

Yucheng Zhou, Jiahao Yuan, Qianning Wang. Draw ALL Your Imagine: A Holistic Benchmark and Agent Framework for Complex Instruction-based Image Generation. (pdf, code).

Selected Publications 📜

Full list on Google Scholar

Yucheng Zhou, Jianbing Shen, Yu Cheng. Weak to Strong Generalization for Large Language Models with Multi-capabilities. ICLR 2025 (pdf).

Yucheng Zhou, Lingran Song, Jianbing Shen. MAM: Modular Multi-Agent Framework for Multi-Modal Medical Diagnosis via Role-Specialized Collaboration. ACL 2025 (pdf, code).

Yucheng Zhou, Lingran Song, Jianbing Shen. Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback. ACL 2025 (pdf).

Hongji Yang, Yucheng Zhou, Wencheng Han, Jianbing Shen. Self-Rewarding Large Vision-Language Models for Optimizing Prompts in Text-to-Image Generation. ACL 2025 (pdf).

Zesheng Shi, Yucheng Zhou, Jing Li, Yuxin Jin, Yu Li, Daojing He, Fangming Liu, Saleh Alharbi, Jun Yu, Min Zhang. Safety Alignment via Constrained Knowledge Unlearning. ACL 2025 (pdf).

Hongji Yang, Wencheng Han, Yucheng Zhou, Jianbing Shen. DC-ControlNet: Decoupling Inter-and Intra-Element Conditions in Image Generation with Diffusion Models. ICCV 2025 (pdf).

Guanjie Chen, Xinyu Zhao, Yucheng Zhou, Xiaoye Qu, Tianlong Chen, Yu Cheng. Towards Stabilized and Efficient Diffusion Transformers through Long-Skip-Connections with Spectral Constraints. ICCV 2025 (pdf, code).

Dubing Chen, Huan Zheng, Yucheng Zhou, Xianfei Li, Wenlong Liao, Tao He, Pai Peng, Jianbing Shen. Causality-Driven Vision-Based 3D Semantic Occupancy Prediction. ICCV 2025.

Chenglin Wang, Yucheng Zhou, Qianning Wang, Zhe Wang, Kai Zhang. ComplexBench-Edit: Benchmarking Complex Instruction-Driven Image Editing via Compositional Dependencies. ACMMM 2025 (pdf, code).

Chenglin Wang, Yucheng Zhou, Zijie Zhai, Jianbing Shen, Kai Zhang. Alternate Geometric and Semantic Denoising Diffusion for Protein Inverse Folding. ECML 2025 (pdf).

Xiang Li, Yucheng Zhou, Laiping Zhao, Jing Li, Fangming Liu. Impromptu Cybercrime Euphemism Detection. COLING 2025 (pdf).

Yucheng Zhou, Xiang Li, Qianning Wang, Jianbing Shen. Visual In-Context Learning for Large Vision-Language Models. ACL 2024 (pdf, code).

Yucheng Zhou, Tao Shen, Xiubo Geng, Chongyang Tao, Jianbing Shen, Guodong Long, Can Xu, Daxin Jiang. Fine-Grained Distillation for Long Document Retrieval. AAAI 2024 (pdf, code).

Wei Tao, Yucheng Zhou, Yanlin Wang, Wenqiang Zhang, Hongyu Zhang, Yu Cheng. MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution. NeurIPS 2024 (pdf, code).

Jiashuo Sun, Jihai Zhang, Yucheng Zhou, Zhaochen Su, Xiaoye Qu, Yu Cheng. SURf: Teaching Large Vision-Language Models to Selectively Utilize Retrieved Information. EMNLP 2024 (pdf, code).

Qian Li, Yucheng Zhou, Cheng Ji, Feihong Lu, Jianian Gong, Shangguang Wang, Jianxin Li. Multi-Modal Inductive Framework for Text-Video Retrieval. ACMMM 2024 (pdf).

Wei Tao, Yucheng Zhou, Yanlin Wang, Hongyu Zhang, Haofen Wang, Wenqiang Zhang. KADEL: Knowledge-Aware Denoising Learning for Commit Message Generation. ACM TOSEM 2024 (pdf).

Yucheng Zhou, Guodong Long. Improving Cross-modal Alignment for Text-Guided Image Inpainting. EACL 2023 (pdf).

Yucheng Zhou, Guodong Long. Style-Aware Contrastive Learning for Multi-Style Image Captioning. EACL 2023 (pdf).

Yucheng Zhou, Guodong Long. Multimodal Event Transformer for Image-guided Story Ending Generation. EACL 2023 (pdf).

Yucheng Zhou, Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Guodong Long, Binxing Jiao, Daxin Jiang. Towards Robust Ranker for Text Retrieval. ACL 2023 (pdf, code).

Yucheng Zhou, Tao Shen, Xiubo Geng, Guodong Long, Daxin Jiang. ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification. ACL 2022 (pdf, code, data).

Yucheng Zhou, Xiubo Geng, Tao Shen, Guodong Long, Daxin Jiang. EventBERT: A Pre-Trained Model for Event Correlation Reasoning. WWW 2022 (pdf, data).

Yucheng Zhou, Xiubo Geng, Tao Shen, Jian Pei, Wenqiang Zhang, Daxin Jiang. Modeling Event-Pair Relations in External Knowledge Graphs for Script Reasoning. ACL 2021 (pdf, data).

Yucheng Zhou, Xiubo Geng, Tao Shen, Wenqiang Zhang, Daxin Jiang. Improving Zero-Shot Cross-lingual Transfer for Multilingual Question Answering over Knowledge Graph. NAACL 2021 (pdf, data).

Experiences 💼

• 2023 - Present, Research Internship at Shanghai AI Lab
• 2020 - 2023, Research Internship at Microsoft

Professional Services 🖊

• Conference Area Chair / Meta-Reviewer:
  ACL (2025), EMNLP (2025), NeurIPS (2025), KDD (2025-2026), AAAI (2026), IJCAI (2023-2025)

• Conference PC Member / Reviewer:
  ICLR (2025), NeurIPS (2024-2025), ICML (2025), ACL (2022-2024), EMNLP (2022-2024), NAACL (2022,2024-2025), COLM (2025), EACL (2024), CVPR (2025), ICCV (2025), ECCV (2024), KDD (2022-2024), SIGIR (2025), AAAI (2024-2026), ACMMM (2022-2025), WSDM (2026), AISTATS (2023-2025)

• Journal Reviewer:
  IEEE Transactions on Affective Computing, Pattern Recognition, Information Fusion, Neural Networks