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Research questionDo newer, larger vision-language models reliably improve autonomous-driving performance without task-specific adaptation?Larger and newer vision-language models often show stronger general reasoning, but that does not necessarily translate into better driving decisions. Autonomous-driving performance can remain inconsistent when models rely on historical actions or struggle to reconcile conflicting visual cues.
AI
Computer Vision
Evaluation & Benchmarks
Multimodal Models
Robotics
Latest papersRecent research connected to this question, newest first.LightEMMA: A Longitudinal Evaluation of Vision-Language Models for Autonomous DrivingThe evidence concerns 15 vision-language models from five model families evaluated with a unified, lightweight protocol on the nuScenes prediction benchmark. The evaluation measures intrinsic driving capability without model-specific adaptation; it does not establish performance in deployed vehicles or broader operational safety.research paper · Sep 2, 2026
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