My full publication list can be found on my Google Scholar profile.


[RL x LLM] Supervised Fine-Tuning as Inverse Reinforcement Learning [Paper]

Hao Sun

[RL x LLM] Reinforcement Learning in the Era of LLMs: What is Essential? What is Needed? [Paper]

Hao Sun


[ICLR 2024] Query-Dependent Prompt Evaluation and Optimization with Inverse RL [Paper] [Code]

Hao Sun, Alihan Hüyük, Mihaela van der Schaar

[NeurIPS 2023] Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples [Paper] [Code (Soon)]

Hao Sun, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar

[NeurIPS 2023] DAUC: a Density-based Approach for Uncertainty Categorization [Paper (To Be Updated)] [Code (Soon)]

Hao Sun ^, Boris van Breugel^, Jonathan Crabbe, Nabeel Seedat, Mihaela van der Schaar

[NeurIPS 2022] Exploiting Reward Shifting in Value-Based DRL [Paper] [Code]

Hao Sun, Lei Han, Rui Yang, Xiaoteng Ma, Jian Guo, Bolei Zhou

[ICLR 2022] Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL [Paper] [Code]

Rui Yang, Yiming Lu, Wenzhe Li, Hao Sun, Meng Fang, Yali Du, Xiu Li, Lei Han, Chongjie Zhang

[IJCAI 2021] Hierarchical Multi-Scale Gaussian Transformer for Stock Movement Prediction [Paper]

Qianggang Ding, Sifan Wu, Hao Sun, Jiadong Guo, Jian Guo

[AAAI 2021] Adaptive Regularization of Labels [Paper]

Qianggang Ding, Sifan Wu, Hao Sun, Jiadong Guo, Shu-Tao Xia

[NeurIPS 2019 (Spotlight)] Policy Continuation with Hindsight Inverse Dynamics [Paper] [Code] [Homepage]

Hao Sun, Zhizhong Li, Xiaotong Liu, Dahua Lin, Bolei Zhou