A new benchmark with clean, corrupted, and text-only driving inputs shows that vision-language models can answer many driving questions without visual information, so standard accuracy metrics overestimate visual grounding.
Spatialvlm: Endow- ing vision-language models with spatial reasoning capabili- ties
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Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives
A new benchmark with clean, corrupted, and text-only driving inputs shows that vision-language models can answer many driving questions without visual information, so standard accuracy metrics overestimate visual grounding.