2024
Fool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support Setting
Maxime Guillaume Kayser, Bayar Menzat, Cornelius Emde, Bogdan Alexandru Bercean, Alex Novak, Abdalá Trinidad Espinosa Morgado +4
EMNLP 2024main
The growing capabilities of AI models are leading to their wider use, including in safety-critical domains. Explainable AI (XAI) aims to make these models safer to use by making their inference process more transparent. However, current explainability methods are seldom evaluated in the way they are…