Study Questions Whether Vision-Language Models Truthfully Explain Autonomous Driving Decisions研究质疑视觉语言模型对自动驾驶决策的真实性解释
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Researchers distinguish between "functional reasoning" (improves task performance) and "faithful reasoning" (truly reflects internal decision logic) in Vision-Language-Action models used for autonomous driving.
Their analysis reveals that current state-of-the-art alignment strategies admit reasoning that masks causal links through confounding factors and lacks environmental grounding, potentially restricting generalization.
Human evaluation of a leading autonomous driving reasoning model shows inconsistent coupling between reasoning quality and task performance, suggesting interpretability gaps in current VLA systems.