Learning Intrinsic Rewards as a Bi-Level Optimization Problem. - Bradly C. Stadie; Lunjun Zhang; Jimmy Ba (UAI, 2020)

World Model as a Graph: Learning Latent Landmarks for Planning. - Lunjun Zhang; Ge Yang 003; Bradly C. Stadie (ICML, 2021)

Understanding Hindsight Goal Relabeling Requires Rethinking Divergence Minimization. - Lunjun Zhang; Bradly C. Stadie (CoRR, 2022)

Learning Realistic Traffic Agents in Closed-loop. - Chris Zhang 001; James Tu; Lunjun Zhang; Kelvin Wong; Simon Suo; Raquel Urtasun (CoRL, 2023)

Towards Unsupervised Object Detection from LiDAR Point Clouds. - Lunjun Zhang; Anqi Joyce Yang; Yuwen Xiong; Sergio Casas 002; Bin Yang 021; Mengye Ren; Raquel Urtasun (CVPR, 2023)

Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion. - Lunjun Zhang; Yuwen Xiong; Ze Yang 003; Sergio Casas 002; Rui Hu 001; Raquel Urtasun (CoRR, 2023)

Learning to Drive via Asymmetric Self-Play. - Chris Zhang 001; Sourav Biswas 001; Kelvin Wong; Kion Fallah; Lunjun Zhang; Dian Chen; Sergio Casas 002; Raquel Urtasun (ECCV (62), 2024)

Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion. - Lunjun Zhang; Yuwen Xiong; Ze Yang 003; Sergio Casas 002; Rui Hu 001; Raquel Urtasun (ICLR, 2024)

Generative Verifiers: Reward Modeling as Next-Token Prediction. - Lunjun Zhang; Arian Hosseini; Hritik Bansal; Mehran Kazemi; Aviral Kumar; Rishabh Agarwal (ICLR, 2025)

Thinking vs. Doing: Agents that Reason by Scaling Test-Time Interaction. - Junhong Shen; Hao Bai; Lunjun Zhang; Yifei Zhou; Amrith Setlur; Shengbang Tong; Diego Caples; Nan Jiang 008; Tong Zhang 001; Ameet Talwalkar; Aviral Kumar (CoRR, 2025)