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. 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 Machine Learning, Natural Language Processing, and Vision and Language. The overarching goal of my work is to advance machine intelligence to serve humanity and assist in exploring the world together. My research pursuits have involved the analysis, training, medical applications, and forward-looking of Large Language Models. Additionally, I am engaged in research on video generation leveraging large language models, aiming to enhance their understanding and generation capabilities within our visual world.

I am always open for research discussions and collaborations.

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, Lingran Song, Jianbing Shen. Training Medical Large Vision-Language Models with Abnormal-Aware Feedback. (pdf).

Chenglin Wang, Yucheng Zhou, Zijie Zhai, Jianbing Shen, Kai Zhang. Diffusion Model with Representation Alignment for Protein Inverse Folding. (pdf).

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

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).

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 / Senior PC Member:
  ACL (2025), ACM KDD (2025), IJCAI (2023-2025)

• Conference PC Member / Reviewer:
  NeurIPS (2024-2025), ICLR (2025), ICML (2025), ACL (2022-2025), EMNLP (2022-2024), NAACL (2022,2024-2025), EACL (2024), CVPR(2025), ICCV(2025), ECCV (2024), ACM KDD (2022-2024), SIGIR (2025), AAAI (2024-2025), ACM Multimedia (2022-2024), AISTATS (2023-2025), ICWSM (2024-2025), ECML-PKDD (2023-2025), ICASSP (2024-2025)

• Journal Reviewer:
  Pattern Recognition, Information Fusion, Neural Networks