Reconciling Faithfulness and Plausibility in Explainable AI: An Empirical Study Across NLP Tasks

Faithfulness and plausibility can be complementary objectives in explainable AI, as traditional perturbation-based methods like Shapley value and LIME can achieve high levels of both accuracy and user accessibility in their explanations.