• Sep. 2024: Our two recent papers “Instruction-Guided Visual Masking” and “Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning” have been accepted in NeurIPS 2024!

• Jul. 2024: Our two recent papers “DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning” and “Instruction-Guided Visual Masking” have won the Outstanding Paper Awards at ICML 2024 Workshop on Multi-modal Foundation Model meets Embodied AI (MFM-EAI).

• May. 2024: Our four recent papers “DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning”, “OMPO: A Unified Framework for Reinforcement Learning under Policy and Dynamics Shifts”, “Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL”, “Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic” have been accepted in ICML 2024!

• Apr. 2024: Our recent survey paper “A Comprehensive Survey of Cross-Domain Policy Transfer for Embodied Agents” has been accepted in IJCAI 2024.

• Jan. 2024: Our four recent papers “Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update”, “Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model”, “Query-Policy Misalignment in Preference-Based Reinforcement Learning”, and “OpenChat: Advancing Open-source Language Models with Mixed-Quality Data” have been accepted in ICLR 2024!

• Oct. 2023: We have released “Data-Driven Control Library (D2C)”, which provides an easy-to-use and comprehensive library for real-world data-driven control & decision-making problems! Project page available at https://github.com/AIR-DI/D2C.

• Sep. 2023: We have released “OpenChat: Advancing Open-source Language Models with Mixed-Quality Data”, which uses ideas from offline RL to fine-tune open-source large language models! Project page available at https://github.com/imoneoi/openchat.

• Sep. 2023: Our two recent papers “Look Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL” and “Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Local Value Regularization” have been accepted in NeurIPS 2023!

🔥 We are hiring: we are looking for postdocs and student interns. If you are interested in the research directions of data-driven decision-making, please feel free to contact us!