collaborators

5 papers

cs.CV2026

Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation

Jie Zhang, Xiaoyue Chen, Anzhe Chen +36

We introduce Qwen-RobotWorld, a language-conditioned video world model for embodied intelligence. With natural language as a unified action interface, it predicts physically ground…

cs.CV2026

GraphWorld: Long-Horizon Planning with World Models for End-to-End Autonomous Driving

Ziying Song, Caiyan Jia, Lin Liu +8

End-to-end autonomous driving has made significant progress by unifying perception, prediction, and planning within a single learning framework, achieving strong performance in sho…

cs.RO2026

Bridging Predictive Uncertainty and Safe Action: Sample-Conditioned Differentiable Planning for Autonomous Driving

Chengzhen Meng, Pei Liu, Zhiyu Huang +2

Complex, dynamic, and interactive driving environments pose significant challenges for autonomous driving, primarily due to the pervasive uncertainty of surrounding traffic. A fund…

cs.RO2026

FeaXDrive: Feasibility-aware Trajectory-Centric Diffusion Planning for End-to-End Autonomous Driving

Baoyun Wang, Zhuoren Li, Ran Yu +6

End-to-end diffusion planning has shown strong potential for autonomous driving, but the physical feasibility of generated trajectories remains insufficiently addressed. In particu…

cs.RO2024

Gen-Drive: Enhancing Diffusion Generative Driving Policies with Reward Modeling and Reinforcement Learning Fine-tuning

Zhiyu Huang, Xinshuo Weng, Maximilian Igl +5

Autonomous driving necessitates the ability to reason about future interactions between traffic agents and to make informed evaluations for planning. This paper introduces the \tex…