AI RESEARCH
FSDAM: Few-Shot Driving Attention Modeling via Vision-Language Coupling
arXiv CS.CV
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ArXi:2511.12708v2 Announce Type: replace Understanding not only where drivers look but also why their attention shifts is essential for interpretable human-AI collaboration in autonomous driving. Driver attention is not purely perceptual but semantically structured. Thus, attention shifts can be learned through minimal semantic supervision rather than dense large-scale annotation.