Preprint
Sep 2026
Long-Horizon Consistent and Interaction-Aware World Models for Multi-Style End-to-End Driving
End-to-end autonomous driving has increasingly adopted world model-based reinforcement learning frameworks to improve learning efficiency through \textit{imagined rollouts}. However, existing world models suffer from three key limitations: temporal inconsistency in long-horizon imagined rollouts, inadequate modeling of...
Yuxuan Han, Kun-Yuan Wu, Liyunong Yang et al.
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