Hi! I’m Chunyang Jiang, currently a second-year Ph.D. student at Hong Kong University of Science and Technology (HKUST), under the supervision of Prof. Wei Xue and Prof. Yike Guo. Before that, I got my Bachelor’s and Master’s degrees at Beihang University (also known as Beijing University of Aeronautics and Astronautics), supervised by Prof. Chunming Hu.

My current research interest locates at self-improvement and synthetic data methodologies for Large Language Models. I have authored several first-author research papers in such areas. I am also interested in opportunities to apply such methodologies to other disciplines, such as science and social science. I am always open to discussions and collaborations. Please feel free to contact me via email rubickjiang[dot]gmail[dot]com.

📖 Education

• 2024.09 - Now, PhD in Artificial Intelligence, Division of Emerging Interdisciplinary Areas, Hong Kong University of Science and Technology.
• 2021.09 - 2024.01, MPhil in Software Engineering, School of Computer Science and Engineering, Beihang University.
• 2017.09 - 2021.06, BSc in Computer Science, School of Computer Science and Engineering, Beihang University.

💻 Internships

• 2025.11 - 2026.04, Research Intern, Fermat Lab, Huawei, HongKong.
• 2023.05 - 2023.08, Applied Research Intern, Department of Tecent News, Tencent, Beijing.

📝 Selected Publications

• Semantic Voting: A Self-Evaluation-Free Approach for Efficient LLM Self-Improvement on Unverifiable Open-ended Tasks. Chunyang Jiang, Yonggang Zhang, Yiyang Cai, Chi-Min Chan, Yulong Liu, Mingming Chen, Wei Xue, Yike Guo. ICLR 2026

• Graceful Forgetting in Generative Language Models. Chunyang Jiang, Chi-min Chan, Yiyang Cai, Yulong Liu, Wei Xue, Yike Guo. EMNLP 2025

• Importance weighting can help large language models self-improve. Chunyang Jiang, Chi-Min Chan, Wei Xue, Qifeng Liu, and Yike Guo. AAAI 2025

• Path Spuriousness-aware Reinforcement Learning for Multi-Hop Knowledge Graph Reasoning. Chunyang Jiang, Tianchen Zhu, Haoyi Zhou, Chang Liu, Ting Deng, Chunming Hu, and Jianxin Li. EACL 2023

• Modeling the Brain’s Grammar: ROI-Guided fMRI Pretraining for Transferable and Interpretable Vision Decoding, Yulong Liu, Hua Xu, Yiyang Cai, Chunyang Jiang, Sirui Han, Yike Guo. CVPR 2026

• Foundation Cures Personalization: Improving Personalized Models’ Prompt Consistency via Hidden Foundation Knowledge. Yiyang Cai, Zhengkai Jiang, Yulong Liu, Chunyang Jiang, Wei Xue, Wenhan Luo, Yike Guo. NeurIPS 2025

• Boosting Policy and Process Reward Models with Monte Carlo Tree Search in Open-Domain QA. Chi-Min Chan, Chunpu Xu, Junqi Zhu, Jiaming Ji, Donghai Hong, Pengcheng Wen, Chunyang Jiang, Zhen Ye, Yaodong Yang, Wei Xue, Sirui Han, Yike Guo. Findings of ACL 2025.

• AIQoSer: Building the efficient Inference-QoS for AI Services. Jianxin Li, Tianchen Zhu, Haoyi Zhou, Qingyun Sun, Chunyang Jiang, Shuai Zhang, Chunming Hu. IWQoS 2022 (Best Paper Award)

🎖 Competition

• 2020.08 The second prize (5/72) in the National Undergraduate Computer System Capability Competition (Compiler Track).

💬 Services

• Journal Reviwer, ACM TIST, IEEE/ACM TASLP, IEEE TIFS, Springer ML, ACM TKDD.
• Conference Reviewer, AAAI 2025, CVPR 2026, ICML 2026.

💬 Teaching

• Data Structures and Algorithms, Teaching Assistant, Beihang University.
• Operating Systems, Teaching Assistant, Beihang University.
• Discrete Mathematics, Teaching Assistant, Beihang University.
• Compilers, Teaching Assistant, Beihang University.
• Cross-Displinary Design Thinking, Teaching Assistant, HKUST.