Qianyue Hao (郝千越)  Ph.D. Candidate, Department of Electronic Engineering, Tsinghua University Email: haoqianyue@hotmail.com CV: [English] [Chinese] [Google Scholar] [ResearchGate]

Biography

I am a fourth-year Ph.D. student at the Department of Electronic Engineering, Tsinghua University, advised by Prof. Yong Li and Prof. Jian Yuan. My research interests lie in Reinforcement Learning (RL) and Large Language Models (LLMs).

Previously, I received my B.E. degree from the Department of Electronic Engineering, Tsinghua University in June 2022.

News

• 2025-09 I have a paper accepted by NeurIPS 2025 as a spotlight!

Conference Publications

• LLM-Explorer: A Plug-in Reinforcement Learning Policy Exploration Enhancement Driven by Large Language Models
  Spotlight paper (top 3.5% paper)
  Qianyue Hao*, Yiwen Song*, Qingmin Liao, Jian Yuan, Yong Li
  The 38th International Conference on Neural Information Processing Systems (NeurIPS 2025)
  
• HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation Prediction
  Qianyue Hao, Jingyang Fan, Fengli Xu, Jian Yuan, Yong Li
  The 37th International Conference on Neural Information Processing Systems (NeurIPS 2024)
  
• CoopRide: Cooperate All Grids in City-Scale Ride-Hailing Dispatching with Multi-Agent Reinforcement Learning
  Jingwei Wang*, Qianyue Hao*, Wenzhen Huang, Xiaochen Fan, Qin Zhang, Zhentao Tang, Bin Wang, Jianye Hao, Yong Li
  The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025)
  
• DyPS: Dynamic Parameter Sharing in Multi-Agent Reinforcement Learning for Spatio-Temporal Resource Allocation
  Jingwei Wang*, Qianyue Hao*, Wenzhen Huang, Xiaochen Fan, Zhentao Tang, Bin Wang, Jianye Hao, Yong Li
  The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)
  
• GAT-MF: Graph Attention Mean Field for Very Large Scale Multi-Agent Reinforcement Learning
  Qianyue Hao, Wenzhen Huang, Tao Feng, Jian Yuan, Yong Li
  The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)
  
• Reinforcement Learning Enhances the Experts: Large-scale COVID-19 Vaccine Allocation with Multi-factor Contact Network
  Qianyue Hao, Wenzhen Huang, Fengli Xu, Kun Tang, Yong Li
  The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022)
  
• Hierarchical Reinforcement Learning for Scarce Medical Resource Allocation with Imperfect Information
  Qianyue Hao, Fengli Xu, Lin Chen, Pan Hui, Yong Li
  The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021)
  
• Understanding the Urban Pandemic Spreading of COVID-19 with Real World Mobility Data
  Qianyue Hao*, Lin Chen*, Fengli Xu, Yong Li
  The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020)
  
• CityLight: A Neighborhood-inclusive Universal Model for Coordinated City-scale Traffic Signal Control
  Jinwei Zeng, Chao Yu, Xinyi Yang, Wenxuan Ao, Qianyue Hao, Jian Yuan, Yong Li, Yu Wang, Huazhong Yang
  The 34th ACM International Conference on Information and Knowledge Management (CIKM 2025)
  

Journal Publications

• Toward Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
  Fengli Xu*, Qianyue Hao*, Chenyang Shao*, Zefang Zong*, Yu Li*, Jingwei Wang, Yunke Zhang, Jingyi Wang, Xiaochong Lan, Jiahui Gong, Tianjian Ouyang, Fanjin Meng, Yuwei Yan, Qinglong Yang, Yiwen Song, Sijian Ren, Xinyuan Hu, Jie Feng, Chen Gao, Yong Li
  Patterns
  
• Hierarchical Multi-agent Model for Reinforced Medical Resource Allocation with Imperfect Information
  Qianyue Hao, Fengli Xu, Lin Chen, Pan Hui, Yong Li
  ACM Transactions on Intelligent Systems and Technology (TIST)
  
• A Survey of Machine Learning for Urban Decision Making: Applications in Planning, Transportation, and Healthcare
  Yu Zheng, Qianyue Hao, Jingwei Wang, Changzheng Gao, Jinwei Chen, Depeng Jin, Yong Li
  ACM Computing Surveys (CSUR)
  

Preprints

• RL of Thoughts: Navigating LLM Reasoning with Inference-time Reinforcement Learning
  Qianyue Hao*, Sibo Li*, Jian Yuan, Yong Li
  
• KeyWorld: Key Frame Reasoning Enables Effective and Efficient World Models
  Sibo Li*, Qianyue Hao*, Yu Shang, Yong Li
  
• Reinforcement Learning Fine-Tuning Enhances Activation Intensity and Diversity in the Internal Circuitry of LLMs
  Honglin Zhang*, Qianyue Hao*, Fengli Xu, Yong Li
  
• Multiple Weaks Win Single Strong: Large Language Models Ensemble Weak Reinforcement Learning Agents into a Supreme One
  Yiwen Song*, Qianyue Hao*, Qingmin Liao, Jian Yuan, Yong Li
  
• AI Expands Scientists' Impact but Contracts Science's Focus
  Qianyue Hao, Fengli Xu, Yong Li, James Evans
  
• Reinforcement Learning in the Era of Large Language Models: Challenges and Opportunities
  Qianyue Hao, Lin Chen, Xiaoqian Qi, Yuan Yuan, Zefang Zong, Hongyi Chen, Keyu Zhao, Shengyuan Wang, Yunke Zhang, Jian Yuan, Yong Li
  
• A Survey on Human-Centric LLMs
  Jing Yi Wang, Nicholas Sukiennik, Tong Li, Weikang Su, Qianyue Hao, Jingbo Xu, Zihan Huang, Fengli Xu, Yong Li
  

Academic Services

• I have served as a reviewer for the following conferences: NeurIPS (2025), ICML (2025), ICLR (2025-2026), AAAI (2026), KDD (2023-2026), WWW (2026), CIKM (2025), SDM (2023)
  
• I have served as a reviewer for the following journals: IMWUT (2025)
  

Awards

• 2025-10 Scholarship for Graduate Students (研究生综合奖学金), Tsinghua University
• 2023-10 Scholarship for Graduate Students (研究生综合奖学金), Department of Electronic Engineering, Tsinghua University
• 2022-06 Outstanding Undergraduate Thesis Award (本科优秀毕业论文), Tsinghua University
• 2021-10 National Scholarship for Undergraduate Students (本科生国家奖学金), Ministry of Education of the PRC
• 2020-10 Scholarship for Undergraduate Students (本科生综合奖学金), Tsinghua University