News!

🇸🇬 (2025.04) I’ll attend ICLR 2025 in-person.

🇺🇸 (2025.03) Guest lecture on Inverse RL Meets LLMs at the UCLA Reinforcement Learning course.

🇺🇸 (2025.02) Attending AAAI 2025 to run the Tutorial: Inverse RL Meets LLMs. Thanks for joining us in Philadelphia! Slide.

📄 (2025.02) Our Reward Model Paper Part IV: Multi-Objective and Personalized Alignment with PCA is online.

📄 (2025.02) Our Reward Model Paper Part III: Infrastructure for Reproducible Reward Model Research os online.

📄 (2025.02) Our Reward Model Paper Part II: Active Reward Modeling is online.

📄 (2025.01) Our Reward Model Paper Part I: Foundation, Theory, and Alternatives is accepted by ICLR as an Oral 🎉. It is an amazing experience to co-lead this paper wity Yunyi and advised by Jef.

🇦🇹 (2024.12) We will run the Tutorial: Inverse RL Meets LLMs at ACL-2025, see you at Vienna!

🇬🇧 (2024.10) New talk on Inverse RL Meets LLMs at the vdsLab2024 OpenHouse and UCLA Zhou Lab. Slide is online

📄 (2024.09) Our Data Centric Reward Modeling paper is accepted by the Journal of Data-Centric Machine Learning Research (DMLR).

🇺🇸 (2024.08) InverseRLignment is presented at the RL beyond reward workshop (accepted with score 9) at the 1-st RLConference, it builds reward models from SFT data..

📄 (2024.05) Our RLHF with Dense Reward paper is accepted by ICML 2024.

🇬🇧 (2024.03) Prompt-OIRL and RATP are featured at the Inspiration Exchange, recording is online .

🇦🇹 (2024.01) 1 RL + LLM Reasoning paper is accepted by ICLR 2024! Prompt-OIRL uses Inverse RL to evaluate and optimize prompts for Math Reasoning.

🇺🇸 (2024.01) Invited talk on RLHF at the Intuit AI Research Forum. slide

🇨🇳 (2023.12) Invited talk on RLHF at the Likelihood Lab slide

🇨🇳 (2023.11) Invited talk on RLHF at the CoAI group, THU.. slide

📄 (2023.10) Prompt-OIRL is selected as an oral presentation 🎉 at the NeurIPS 2023 ENLSP workshop!

📄 (2023.10) I wrote an article to share my thoughts as an RL researcher in the Era of LLMs.

📄 (2023.09) 2 papers on Interpretable Offline RL and Interpretable Uncertainty Quantification are accepted by NeurIPS 2023.

🇨🇳 (2023.9) Invited talk on “Reinforcement Learning in the Era of LLMs” at Kuaishou Research. slide is online

📄 (2023.2) 2 papers are accepted by AISTATS 2023.

🇮🇪 (2022.11) Invited talk on value-based DRL at HW Cloud Research. slide is online

📄 (2022.9) 1 paper on Value-Based DeepRL is accepted by NeurIPS 2022. 2 papers are presented at the FMDM workshop, and 2 papers are presented at the DeepRL workshop.

📄 (2022.1) 1 paper on Offline GCRL is accepted by ICLR 2022.