Inverse Classification for Comparison-based Interpretability in Machine Learning. - Thibault Laugel; Marie-Jeanne Lesot; Christophe Marsala; Xavier Renard; Marcin Detyniecki (CoRR, 2017)

Comparison-Based Inverse Classification for Interpretability in Machine Learning. - Thibault Laugel; Marie-Jeanne Lesot; Christophe Marsala; Xavier Renard; Marcin Detyniecki (IPMU (1), 2018)

Detecting Potential Local Adversarial Examples for Human-Interpretable Defense. - Xavier Renard; Thibault Laugel; Marie-Jeanne Lesot; Christophe Marsala; Marcin Detyniecki (Nemesis/UrbReas/SoGood/IWAISe/GDM@PKDD/ECML, 2018)

Defining Locality for Surrogates in Post-hoc Interpretablity. - Thibault Laugel; Xavier Renard; Marie-Jeanne Lesot; Christophe Marsala; Marcin Detyniecki (CoRR, 2018)

The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations. - Thibault Laugel; Marie-Jeanne Lesot; Christophe Marsala; Xavier Renard; Marcin Detyniecki (IJCAI, 2019)

Unjustified Classification Regions and Counterfactual Explanations in Machine Learning. - Thibault Laugel; Marie-Jeanne Lesot; Christophe Marsala; Xavier Renard; Marcin Detyniecki (ECML/PKDD (2), 2019)

Issues with post-hoc counterfactual explanations: a discussion. - Thibault Laugel; Marie-Jeanne Lesot; Christophe Marsala; Marcin Detyniecki (CoRR, 2019)

Imperceptible Adversarial Attacks on Tabular Data. - Vincent Ballet; Xavier Renard; Jonathan Aigrain; Thibault Laugel; Pascal Frossard; Marcin Detyniecki (CoRR, 2019)

Local Post-hoc Interpretability for Black-box Classifiers. (Interprétabilité Locale Post-hoc des Algorithmes de Classification "Boîtes noires"). - Thibault Laugel (2020)

How to Choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice. - Tom Vermeire; Thibault Laugel; Xavier Renard; David Martens; Marcin Detyniecki (PKDD/ECML Workshops (1), 2021)

Understanding Prediction Discrepancies in Machine Learning Classifiers. - Xavier Renard; Thibault Laugel; Marcin Detyniecki (CoRR, 2021)

On the overlooked issue of defining explanation objectives for local-surrogate explainers. - Rafael Poyiadzi; Xavier Renard; Thibault Laugel; Raúl Santos-Rodríguez; Marcin Detyniecki (CoRR, 2021)

Understanding surrogate explanations: the interplay between complexity, fidelity and coverage. - Rafael Poyiadzi; Xavier Renard; Thibault Laugel; Raúl Santos-Rodríguez; Marcin Detyniecki (CoRR, 2021)

Integrating Prior Knowledge in Post-hoc Explanations. - Adulam Jeyasothy; Thibault Laugel; Marie-Jeanne Lesot; Christophe Marsala; Marcin Detyniecki (IPMU (2), 2022)

Intégration de connaissances dans les méthodes d'explications post-hoc. - Adulam Jeyasothy; Thibault Laugel; Marie-Jeanne Lesot; Christophe Marsala; Marcin Detyniecki (LFA, 2022)

Achieving Diversity in Counterfactual Explanations: a Review and Discussion. - Thibault Laugel; Adulam Jeyasothy; Marie-Jeanne Lesot; Christophe Marsala; Marcin Detyniecki (FAccT, 2023)

Knowledge Integration in XAI with Gödel Integrals. - Adulam Jeyasothy; Agnès Rico; Marie-Jeanne Lesot; Christophe Marsala; Thibault Laugel (FUZZ, 2023)

When Mitigating Bias is Unfair: A Comprehensive Study on the Impact of Bias Mitigation Algorithms. - Natasa Krco; Thibault Laugel; Jean-Michel Loubes; Marcin Detyniecki (CoRR, 2023)

A general framework for personalising post hoc explanations through user knowledge integration. - Adulam Jeyasothy; Thibault Laugel; Marie-Jeanne Lesot; Christophe Marsala; Marcin Detyniecki (Int. J. Approx. Reason., 2023)

On the Fairness ROAD: Robust Optimization for Adversarial Debiasing. - Vincent Grari; Thibault Laugel; Tatsunori Hashimoto; Sylvain Lamprier; Marcin Detyniecki (ICLR, 2024)

Why do explanations fail? A typology and discussion on failures in XAI. - Clara Bove; Thibault Laugel; Marie-Jeanne Lesot; Charles Tijus; Marcin Detyniecki (CoRR, 2024)

Post-processing fairness with minimal changes. - Federico Di Gennaro; Thibault Laugel; Vincent Grari; Xavier Renard; Marcin Detyniecki (CoRR, 2024)

Understanding prediction discrepancies in classification. - Xavier Renard; Thibault Laugel; Marcin Detyniecki (Mach. Learn., 2024)

SAKE: Steering Activations for Knowledge Editing. - Marco Scialanga; Thibault Laugel; Vincent Grari; Marcin Detyniecki (ACL (1), 2025)

When Mitigating Bias is Unfair: Multiplicity and Arbitrariness in Algorithmic Group Fairness. - Natasa Krco; Thibault Laugel; Vincent Grari; Jean-Michel Loubes; Marcin Detyniecki (SaTML, 2025)

Controlled Model Debiasing through Minimal and Interpretable Updates. - Federico Di Gennaro; Thibault Laugel; Vincent Grari; Marcin Detyniecki (Trans. Mach. Learn. Res., 2025)

Metric assessment protocol in the context of answer fluctuation on MCQ tasks. - Ekaterina Goliakova; Xavier Renard; Marie-Jeanne Lesot; Thibault Laugel; Christophe Marsala; Marcin Detyniecki (CoRR, 2025)