Traditional driver’s skill tests primarily assess whether candidates meet specific standards in prescribed tasks, which often fails to fully reflect their overall driving performance in real-world sce
In this work, we investigate the problem of Model-Agnostic Zero-Shot Classification (MA-ZSC), which refers to training non-specific classification architectures (downstream models) to classify real im