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cs.RO2026
Long-Horizon Consistent and Interaction-Aware World Models for Multi-Style End-to-End Driving
Yuxuan Han, Kunyuan Wu, Liyunong Yang +4
End-to-end autonomous driving has increasingly adopted world model-based reinforcement learning frameworks to improve learning efficiency through \textit{imagined rollouts}. Howeve…
cs.RO2026
LiDAR Teach, Radar Repeat: Robust Cross-Modal Navigation in Degenerate and Varying Environments
Renxiang Xiao, Yichen Chen, Yuanfan Zhang +5
Long-term autonomy requires robust navigation in environments subject to dynamic and static changes, as well as adverse weather conditions. Teach-and-Repeat (T\&R) navigation offer…
cs.RO2026
AppleVLM: End-to-end Autonomous Driving with Advanced Perception and Planning-Enhanced Vision-Language Models
Yuxuan Han, Kunyuan Wu, Qianyi Shao +6
End-to-end autonomous driving has emerged as a promising paradigm integrating perception, decision-making, and control within a unified learning framework. Recently, Vision-Languag…