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cs.CV2025
RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learning
Hao Gao, Shaoyu Chen, Bo Jiang +11
Existing end-to-end autonomous driving (AD) algorithms typically follow the Imitation Learning (IL) paradigm, which faces challenges such as causal confusion and an open-loop gap.…
cs.RO2025★ 1 cited
RoboBERT: An End-to-end Multimodal Robotic Manipulation Model
Sicheng Wang, Sheng Liu, Weiheng Wang +2
Embodied intelligence seamlessly integrates vision, language, and action.~However, most multimodal robotic models rely on massive fine-tuning, incurring high time and hardware cost…