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   Yao-Xiang Ding   丁尧相


     Assistant Professor


       State Key Lab of CAD & CG
       College of Computer Science & Technology
       Zhejiang University

      Email: dingyx.gm at gmail.com (preferred), yxding at zju.edu.cn
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Wir müssen wissen. Wir werden wissen. 憧憬光明，就不会惧怕黑暗。

Biography

I am a tenure-track assistant professor in the State Key Lab of CAD & CG and College of Computer Science & Technology, Zhejiang University, as a member of the GAPS group led by Prof. Kun Zhou. I received Ph.D. degree in computer science from LAMDA, Nanjing University in 2020, advised by Prof. Zhi-Hua Zhou. Before that, I received M.Sc. degree in computer science from Peking University in 2014 and B.Sc. degree in mechanical engineering from University of Science and Technology Beijing in 2011.

Research Interests

I work on building and understanding intelligent heuristics in the field of machine learning, with special interests on the following topics:

• neurosymbolic visual understanding, generation, and decision making: bridging symbolic (logical, causal) inference and neural network learning to jointly solve system-1 and system-2 visual learning problems.
• active learning, machine teaching, and pretrained model reuse: understanding how prior information can help reduce the sample complexity.

Our small research subgroup is named "future-item". [GitHub]
• For prospective students who are interested to work with me, please read this note first.

Selected Research Papers

Full Publication List

Preprints:

• Yaoli Liu, Yao-Xiang Ding, Kun Zhou, "FreeFuse: Multi-Subject LoRA Fusion via Auto Masking at Test Time", arxiv preprint 2510.23515.

• Yifei Peng, Yaoli Liu, Enbo Xia, Yu Jin, Wang-Zhou Dai, Zhong Ren, Yao-Xiang Ding, Kun Zhou, "Abductive Logical Rule Induction by Bridging Inductive Logic Programming and Multimodal Large Language Models", arxiv preprint 2509.21874.

Conference Papers:

• Yifei Peng, Zijie Zha, Yu Jin, Zhexu Luo, Wang-Zhou Dai, Zhong Ren, Yao-Xiang Ding, Kun Zhou, "Generating by Understanding: Neural Visual Generation with Logical Symbol Groundings", KDD, 2025. [arXiv]

• Bohong Chen, Yumeng Li, Yao-Xiang Ding, Tianjia Shao, Kun Zhou, "Enabling Synergistic Full-Body Control in Prompt-Based Co-Speech Motion Generation", ACM Multimedia, 2024.

• Xin-Qiang Cai, Yao-Xiang Ding, Zi-Xuan Chen, Yuan Jiang, Masashi Sugiyama, Zhi-Hua Zhou, "Seeing Differently, Acting Similarly: Heterogeneously Observable Imitation Learning", ICLR (spotlight), 2023.

• Yao-Xiang Ding, Xi-Zhu Wu, Kun Zhou, Zhi-Hua Zhou, "Pre-Trained Model Reusability Evaluation for Small-Data Transfer Learning", NeurIPS, 2022.

• Xin-Qiang Cai, Yao-Xiang Ding, Yuan Jiang, Zhi-Hua Zhou, "Imitation Learning from Pixel-Level Demonstrations by HashReward", AAMAS (long paper), 2021.

• Yao-Xiang Ding, Zhi-Hua Zhou, "Preference Based Adaptation for Learning Objectives", NeurIPS, 2018.

Journal Articles:

• Jingming Liu, Yumeng Li, Boyuan Xiao, Yichang Jian, Ziang Qin, Tianjia Shao, Yao-Xiang Ding, Kun Zhou, "Autonomous Imagination: Closed-Loop Decomposition of Visual-to-Textual Conversion in Visual Reasoning for Multimodal Large Language Models", Transactions on Machine Learning Research (TMLR), 2025. [Project Page]

• Yumeng Li, Bohong Chen, Zhong Ren, Yao-Xiang Ding, Libin Liu, Tianjia Shao, Kun Zhou, "CPoser: An Optimization-after-Parsing Approach for Text-to-Pose Generation Using Large Language Models", ACM Transactions on Graphics (TOG) (SIGGRAPH Asia journal track paper), 2024.

• Yu-Cheng He, Yao-Xiang Ding, Zhi-Hua Zhou, "Mechanism Design for Requester-Platform Strategies Under the Three-Party Crowdsourcing Market", Journal of Computer Research And Development (in Chinese, CCFAI 2021 conference best paper award), 2021.

• Yao-Xiang Ding, Zhi-Hua Zhou, "Crowdsourcing with Unsure Option", Machine Learning Journal, 2018.

Activities

• Model Reuse: Theories and Applications, Tutorial on AAAI'24, co-organized with Dr. Han-Jia Ye. [Slides of part1][Slides of part2]

Courses

• Advanced Data Structures and Algorithm Analysis, Undergraduate, Zhejiang University. Latest version: [Fall and Winter 2025]

• Introduction to Machine Learning (co-teach with Prof. Yingchun Yang, Dr. Qian Zheng and Dr. Chaochao Chen), Graduate, Spring 2023, Zhejiang University. [Slides of Lecture 7][Slides of Lecture 8]

• Introduction to Artificial Intelligence, Undergraduate, Fall and Winter 2022, Zhejiang University.

Students

Current Students:

• PhD: Yifei Peng, Zijie Zha, Boyuan Xiao.

• Master: Ziang Qin, Jingming Liu, Junhua Shen, Enbo Xia, Yaoli Liu.

• Undergraduate: Yichang Jian, Yihan Wu, Zhouyue Qian, Pu Wang.

Alumni (with graduate destinations):

• Master: Yu Jin (Engineer@SPD Bank).

• Undergraduate: Yi Jiang (PhD student@ZJU), Libin Sun (master student@NYU), Zhexu Luo (master student@Penn).
Latest update: 2026.2.10.