Model Bias Detection

This paper introduces a novel ’network surgery’ approach that integrates CNNs with CLIP to provide caption-based explanations. By moving beyond potentially misleading saliency maps, this method identifies the dominant semantic concepts driving a model’s prediction, enabling better detection of spurious biases and improving overall model robustness.