More Than Meets the Eye? Uncovering the Reasoning-Planning Disconnect in Training Vision-Language Driving Models

This research explores whether reasoning in vision-language driving models causally influences planning. Using a new dataset, DriveMind, the authors find that planning is primarily driven by priors rather than reasoning, proposing a decoupling hypothesis and introducing a diagnostic tool for model evaluation.