Identifying Confusion Trends in Concept-based XAI for Multi-Label Classification
This work explores CXAI use cases in multi-label classification by training two DNNs, VGG16 and ResNet50, on the 20 most annotated labels in the MS-COCO dataset and demonstrates the potential of CXAI to enhance the understanding of model generalizability and to diagnose bias instigated by the dataset.