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LightEMMA: A Longitudinal Evaluation of Vision-Language Models for Autonomous Driving
Rapid advances in vision-language models (VLMs) have generated growing interest in their application to autonomous driving. A prevailing assumption is that successive VLM generations will continually improve driving performance and eventually outperform state-of-the-art methods. To systematically ex
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