Interpretable Modeling of Driver Attention Shifts with a Vision--Language Model

ArXi:2508.05852v2 Announce Type: replace Driver gaze is commonly modeled as a spatial heatmap, but heatmaps alone are difficult for humans to interpret because they do not explain which road object or region is being monitored or why an attention shift may matter. This study examines whether minimal human-grounded supervision can steer a vision--language model toward interpretable descriptions of driver attention shifts.