100 citations · 395 across the 34 of their papers we have counts for
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cs.RO2025
LTDA-Drive: LLMs-guided Generative Models based Long-tail Data Augmentation for Autonomous Driving
Mahmut Yurt, Xin Ye, Yunsheng Ma +5
3D perception plays an essential role for improving the safety and performance of autonomous driving. Yet, existing models trained on real-world datasets, which naturally exhibit l…
cs.RO2025
AdaWM: Adaptive World Model based Planning for Autonomous Driving
Hang Wang, Xin Ye, Feng Tao +5
World model based reinforcement learning (RL) has emerged as a promising approach for autonomous driving, which learns a latent dynamics model and uses it to train a planning polic…
cs.RO2024
LORD: Large Models based Opposite Reward Design for Autonomous Driving
Xin Ye, Feng Tao, Abhirup Mallik +2
Reinforcement learning (RL) based autonomous driving has emerged as a promising alternative to data-driven imitation learning approaches. However, crafting effective reward functio…