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A three-stage pipeline that transforms abundant unlabelled observation-trajectory pairs into a substrate for language-conditioned control and achieves a Driving Score of 87.98 and a Success Rate of 70.46%, matching or surpassing fully supervised baselines on the closed-loop Bench2Drive benchmark.
Recurrent Action Memory (RAM) is proposed, a lightweight module that conditions action prediction on previous action tokens, providing temporal context critical for manoeuvres such as overtaking and emergency braking.
It is found that configuration shift consistently erodes CP validity, often driving empirical coverage below the target, and coverage lower bounds are derived that attribute this loss to a discrepancy between calibration and test score distributions.
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