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cs.CV2026
DriveReward: A Comprehensive Dataset and Generative Vision-Language Reward Model for Autonomous Driving
Qimao Chen, Fang Li, Yuechen Luo +11
Reward models play a pivotal role in reinforcement learning (RL) and multi-modal trajectory selection for autonomous driving. However, acquiring such rewards typically relies on ha…
cs.CV2026
Unleashing VLA Potentials in Autonomous Driving via Explicit Learning from Failures
Yuechen Luo, Qimao Chen, Fang Li +5
Vision-Language-Action (VLA) models for autonomous driving often hit a performance plateau during Reinforcement Learning (RL) optimization. This stagnation arises from exploration…
cs.CV2026
VILTA: A VLM-in-the-Loop Adversary for Enhancing Driving Policy Robustness
Qimao Chen, Fang Li, Shaoqing Xu +9
The safe deployment of autonomous driving (AD) systems is fundamentally hindered by the long-tail problem, where rare yet critical driving scenarios are severely underrepresented i…