The Trade-Off Between Accuracy and Agreement in AI Models

This section analyzes PEAR's effectiveness by calculating consensus across six recognized explainer agreement measures, including as pairwise rank agreement, rank correlation, and feature agreement. PEAR training not only increases agreement between the explainers utilized in the loss (Grad and IntGrad), but it also makes significant progress in generalizing to explainers that are not visible, such LIME and SHAP.