2 papers
cs.LG2026
Knowing What You Cannot Explain: Learning to Reject Low-Quality Explanations
Luca Stradiotti, Dario Pesenti, Stefano Teso +1
Learning to Reject (LtR) frameworks allow ML models to abstain from uncertain predictions and promote user trust. However, since current LtR strategies focus solely on predictive p…
cs.AI2025
Human Cognitive Biases in Explanation-Based Interaction: The Case of Within and Between Session Order Effect
Dario Pesenti, Alessandro Bogani, Katya Tentori +1
Explanatory Interactive Learning (XIL) is a powerful interactive learning framework designed to enable users to customize and correct AI models by interacting with their explanatio…