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Task-Aligned Stability Analysis of Vision-Language Models for Autonomous Driving Hazard Detection
Vision-language models (VLMs) are increasingly used for scene understanding in autonomous driving, but robustness analysis often relies on task-agnostic embedding stability alone. We study whether corruption-induced embedding drift predicts changes in a task-aligned hazard score derived from CLIP im
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