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cs.CV2026
How Well Do Vision-Language Models Understand Sequential Driving Scenes? A Sensitivity Study
Roberto Brusnicki, Mattia Piccinini, Johannes Betz
Vision-Language Models (VLMs) are increasingly proposed for autonomous driving tasks, yet their performance on sequential driving scenes remains poorly characterized, particularly…
cs.CV2025
Can VLMs Unlock Semantic Anomaly Detection? A Framework for Structured Reasoning
Roberto Brusnicki, David Pop, Yuan Gao +2
Autonomous driving systems remain critically vulnerable to the long-tail of rare, out-of-distribution semantic anomalies. While VLMs have emerged as promising tools for perception,…