| 2026 | AAAI | RLKD: Distilling LLMs' Reasoning via Reinforcement Learning. | Shicheng Xu, Liang Pang, Yunchang Zhu, Jia Gu, Zihao Wei, Jingcheng Deng, Feiyang Pan, Huawei Shen, Xueqi Cheng |
| 2024 | ICONIP | Style Miner: Find Significant and Stable Factors in Time Series with Constrained Reinforcement Learning. | Dapeng Li, Feiyang Pan, Jia He, Zhiwei Xu, Dandan Tu, Guoliang Fan |
| 2023 | AAAI | Gradient-Adaptive Pareto Optimization for Constrained Reinforcement Learning. | Zixian Zhou, Mengda Huang, Feiyang Pan, Jia He, Xiang Ao, Dandan Tu, Qing He |
| 2023 | KDD | Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning. | Shuo Yu, Hongyan Xue, Xiang Ao, Feiyang Pan, Jia He, Dandan Tu, Qing He |
| 2022 | IJCAI | Learn Continuously, Act Discretely: Hybrid Action-Space Reinforcement Learning For Optimal Execution. | Feiyang Pan, Tongzhe Zhang, Ling Luo, Jia He, Shuoling Liu |
| 2021 | WWW | GuideBoot: Guided Bootstrap for Deep Contextual Banditsin Online Advertising. | Feiyang Pan, Haoming Li, Xiang Ao, Wei Wang, Yanrong Kang, Ao Tan, Qing He |
| 2021 | SIGIR | Follow the Prophet: Accurate Online Conversion Rate Prediction in the Face of Delayed Feedback. | Haoming Li, Feiyang Pan, Xiang Ao, Zhao Yang, Min Lu, Junwei Pan, Dapeng Liu, Lei Xiao, Qing He |
| 2020 | ACML | CCA-Flow: Deep Multi-view Subspace Learning with Inverse Autoregressive Flow. | Jia He, Feiyang Pan, Fuzhen Zhuang, Qing He |
| 2020 | WWW | Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions. | Feiyang Pan, Xiang Ao, Pingzhong Tang, Min Lu, Dapeng Liu, Lei Xiao, Qing He |
| 2020 | SIGIR | GoChat: Goal-oriented Chatbots with Hierarchical Reinforcement Learning. | Jianfeng Liu, Feiyang Pan, Ling Luo |
| 2019 | AAAI | Policy Optimization with Model-Based Explorations. | Feiyang Pan, Qingpeng Cai, Anxiang Zeng, Chun-Xiang Pan, Qing Da, Hua-Lin He, Qing He, Pingzhong Tang |
| 2019 | EMNLP | Reading Like HER: Human Reading Inspired Extractive Summarization. | Ling Luo, Xiang Ao, Yan Song, Feiyang Pan, Min Yang, Qing He |
| 2019 | WWW | Policy Gradients for Contextual Recommendations. | Feiyang Pan, Qingpeng Cai, Pingzhong Tang, Fuzhen Zhuang, Qing He |
| 2019 | SIGIR | Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings. | Feiyang Pan, Shuokai Li, Xiang Ao, Pingzhong Tang, Qing He |
| 2018 | IJCAI | Beyond Polarity: Interpretable Financial Sentiment Analysis with Hierarchical Query-driven Attention. | Ling Luo, Xiang Ao, Feiyang Pan, Jin Wang, Tong Zhao, Ningzi Yu, Qing He |