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K-Risk reveals that a knowledge-augmented dataset can significantly improve the understanding and management of high-risk driving scenarios in autonomous vehicles.
QGF achieves superior performance in reinforcement learning by optimizing policies solely at test time, sidestepping the instability of traditional training methods.
