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Yu, Zhouliang I'm Zhouliang Yu (郁昼亮), a PhD student at the Scalable Principles for Learning and Reasoning Lab (SphereLab) in the Chinese University of Hong Kong, Department of Computer Science & Engineering, advised by Prof. Weiyang Liu. My research focuses on large language models, deep learning, reinforcement learning, and formal reasoning. My primary research (2024–2027) centers on exploration-based reinforcement learning for formal mathematics reasoning using agentic large language models. I am also actively learning RL infrastructure to support large model training. Beyond my core focus, I am interested in applications of reinforcement learning in model-based embodied AI and scientific discovery through formal verification (I have not yet published in these areas), such as projects like Scientist AI and PhysLean. Previously, I spent one year as a PhD student at HKUST advised by Prof. Yike Guo at HKGAI. I hold a bachelor's degree from the CUHK-SZ, majored in CS. Email / CV / Google Scholar / Twitter / Github |
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ResearchMost of my research is about reinforcement learning, large language models, AI4Math, and embodied AI. Some papers are highlighted. |
Mathematical Reasoning & AI4Math |
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Formalmath: Benchmarking formal mathematical reasoning of large language models
Zhouliang Yu, Ruotian Peng, Keyi Ding, Yizhe Li, Zhongyuan Peng, Minghao Liu, Yifan Zhang, Zheng Yuan, Huajian Xin, Wenhao Huang, Yandong Wen, Ge Zhang, Weiyang Liu arXiv preprint arXiv:2505.02735, 2025 |
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Kimina-prover preview: Towards large formal reasoning models with reinforcement learning
Haiming Wang, Mert Unsal, Xiaohan Lin, Mantas Baksys, Junqi Liu, Zhouliang Yu, et al. arXiv preprint arXiv:2504.11354, 2025 |
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CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization
Zhongyuan Peng, Yifan Yao, Kaijing Ma, Shuyue Guo, Yizhe Li, Yichi Zhang, Chenchen Zhang, Yifan Zhang, Zhouliang Yu, et al. arXiv preprint arXiv:2507.06181, 2025 |
Large Language Models |
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Map-neo: Highly capable and transparent bilingual large language model series
Ge Zhang, Scott Qu, Jiaheng Liu, Chenchen Zhang, Chenghua Lin, Chow Leuang Yu (Core Contributor, authored with my Cantonese name), et al. Technical Report, 2024 |
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Chinese tiny llm: Pretraining a chinese-centric large language model
Xinwei Du, Zhouliang Yu (Co-First Author), Songyang Gao, Ding Pan, Yuyang Cheng, Ziyang Ma, Ruibin Yuan, Xingwei Qu, Jiaheng Liu, Tianyu Zheng, Xinchen Luo, Guorui Zhou, Wenhu Chen, Ge Zhang Conference on Language Modeling, 2024 |
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Codeeditorbench: Evaluating code editing capability of large language models
Jiawei Guo, Ziming Li, Xueling Liu, Kaijing Ma, Tianyu Zheng, Zhouliang Yu, Dawei Pan, Yizhi Li, Ruibo Liu, Yue Wang, Shuyue Guo, et al. arXiv preprint arXiv:2404.03543, 2024 |
Reinforcement Learning |
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Asp: Learn a universal neural solver!
Chenguang Wang, Zhouliang Yu, Stephen McAleer, Tianshu Yu, Yaodong Yang IEEE Transactions on Pattern Analysis and Machine Intelligence, 46 (6), 4102-4114, 2024 |
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Generating Symbolic World Models via Test-time Scaling of Large Language Models
Zhouliang Yu, Yuhuan Yuan, Tim Z. Xiao, Fuxiang Frank Xia, Jie Fu, Ge Zhang, Ge Lin, Weiyang Liu Transactions on Machine Learning Research, 2025 |
Embodied AI & Robotics |
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ManiFoundation Model for General-Purpose Robotic Manipulation of Contact Synthesis with Arbitrary Objects and Robots
Zhixuan Xu, Chongkai Gao, Zixuan Liu, Gang Yang, Chenrui Tie, Haozhuo Zheng, Haoyu Zhou, Weikun Peng, Debang Wang, Tianrun Hu, Tianyi Chen, Zhouliang Yu, Lin Shao International Conference on Intelligent Robots and Systems (Oral), 2024 |
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Multireact: Multimodal tools augmented reasoning-acting traces for embodied agent planning
Zhouliang Yu, Jie Fu, Yue Mu, Chenguang Wang, Lin Shao, Yaodong Yang Robot Learning Workshop at NeurIPS 2023 (Oral), 2023 |
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