Model Interpretability and Explainability Questions

Discuss techniques for understanding what models learn: attention visualization, feature importance methods (SHAP, LIME), saliency maps, concept-based explanations. Understand the difference between post-hoc explainability and inherent interpretability. Discuss trade-offs with model complexity.