All Publications


  • Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer Liu, Z., Lu, M., Zhang, S., Liu, B., Guo, H., Yang, Y., Blanchet, J., Wang, Z. edited by Globerson, A., Mackey, L., Belgrave, D., Fan, A., Paquet, U., Tomczak, J., Zhang, C. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2024
  • Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms Lu, M., Zhong, H., Zhang, T., Blanchet, J. edited by Globerson, A., Mackey, L., Belgrave, D., Fan, A., Paquet, U., Tomczak, J., Zhang, C. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2024
  • Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage Blanchet, J., Lu, M., Zhang, T., Zhong, H. edited by Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2023
  • Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration Liu, Z., Lu, M., Xiong, W., Zhong, H., Hu, H., Zhang, S., Zheng, S., Yang, Z., Wang, Z. edited by Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S. NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2023