3 papers
cs.CV2026
Interpretable Modeling of Driver Attention Shifts with a Vision-Language Model
Kaiser Hamid, Khandakar Ashrafi Akbar, Peihang Li +1
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 moni…
cs.CL2026
ICR-Drive: Instruction Counterfactual Robustness for End-to-End Language-Driven Autonomous Driving
Kaiser Hamid, Can Cui, Nade Liang
Recent progress in vision-language-action (VLA) models has enabled language-conditioned driving agents to execute natural-language navigation commands in closed-loop simulation, ye…
cs.CV2026
FSDAM: Few-Shot Driving Attention Modeling via Vision-Language Coupling
Kaiser Hamid, Can Cui, Khandakar Ashrafi Akbar +2
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 p…