A comparative analysis of rule-based, model-agnostic methods for explainable artificial intelligence. - Giulia Vilone; Lucas Rizzo; Luca Longo (AICS, 2020)

Explainable Artificial Intelligence: a Systematic Review. - Giulia Vilone; Luca Longo (CoRR, 2020)

A Quantitative Evaluation of Global, Rule-Based Explanations of Post-Hoc, Model Agnostic Methods. - Giulia Vilone; Luca Longo (Frontiers Artif. Intell., 2021)

Notions of explainability and evaluation approaches for explainable artificial intelligence. - Giulia Vilone; Luca Longo (Inf. Fusion, 2021)

Classification of Explainable Artificial Intelligence Methods through Their Output Formats. - Giulia Vilone; Luca Longo (Mach. Learn. Knowl. Extr., 2021)

An XAI method for the Automatic Formation of an Abstract Argumentation Framework from a Neural Network and its Objective Evaluation. - Giulia Vilone; Luca Longo (ArgXAI@COMMA, 2022)

A Novel Human-Centred Evaluation Approach and an Argument-Based Method for Explainable Artificial Intelligence. - Giulia Vilone; Luca Longo (AIAI (1), 2022)

Development of a Human-Centred Psychometric Test for the Evaluation of Explanations Produced by XAI Methods. - Giulia Vilone; Luca Longo (xAI (3), 2023)

An Examination of the Effect of the Inconsistency Budget in Weighted Argumentation Frameworks and their Impact on the Interpretation of Deep Neural Networks. - Giulia Vilone; Luca Longo (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2023)

Aligning XAI with EU Regulations for Smart Biomedical Devices: A Methodology for Compliance Analysis. - Francesco Sovrano; Michael Lognoul; Giulia Vilone (ECAI, 2024)

Model agnostic calibration of image classifiers. - Paolo Giudici; Giulia Vilone (xAI (Late-breaking Work, Demos, Doctoral Consortium), 2024)

On the Explainability of Financial Robo-Advice Systems. - Giulia Vilone; Francesco Sovrano; Michaël Lognoul (xAI (4), 2024)