| 2026 | ACL | CE-RM: A Pointwise Generative Reward Model Optimized via Two-Stage Rollout and Unified Criteria. | Xinyu Hu, Yancheng He, Weixun Wang, Tao Feng, Li Lin, Jiashun Liu, Wenbo Su, Bo Zheng, Xiaojun Wan |
| 2025 | AAAI | Flow Factorization for Efficient Generative Flow Networks. | Jiashun Liu, Chunhui Li, Cheng-Hao Liu, Dianbo Liu, Qingpeng Cai, Ling Pan |
| 2025 | ICLR | Neuroplastic Expansion in Deep Reinforcement Learning. | Jiashun Liu, Johan S. Obando-Ceron, Aaron C. Courville, Ling Pan |
| 2025 | ICML | The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning. | Jiashun Liu, Johan S. Obando-Ceron, Pablo Samuel Castro, Aaron C. Courville, Ling Pan |
| 2024 | CVPR | Generate Subgoal Images Before Act: Unlocking the Chain-of-Thought Reasoning in Diffusion Model for Robot Manipulation with Multimodal Prompts. | Fei Ni, Jianye Hao, Shiguang Wu, Longxin Kou, Jiashun Liu, Yan Zheng, Bin Wang, Yuzheng Zhuang |
| 2024 | ICML | Unlock the Cognitive Generalization of Deep Reinforcement Learning via Granular Ball Representation. | Jiashun Liu, Jianye Hao, Yi Ma, Shuyin Xia |
| 2024 | UAI | Hybrid CtrlFormer: Learning Adaptive Search Space Partition for Hybrid Action Control via Transformer-based Monte Carlo Tree Search. | Jiashun Liu, Xiaotian Hao, Jianye Hao, Yan Zheng, Yujing Hu, Changjie Fan, Tangjie Lv, Zhipeng Hu |