Explainable AI is a field that has emerged with the boom in machine learning and the opacity of the most precise models (such as deep neural networks). Human users of AI systems indeed need safeguards to avoid taking erroneous predictions as correct, and the ability to provide explanations of the predictions made is one way of rejecting such predictions. This need is critical when AI components are used in sensitive applications, and the explanation requirement is a matter of regulation in Europe (with the RGPD since 2018 and with the AI Act now). For these reasons, we had chosen to put the theme of “Explainable AI” at the center of CRIL’s scientific project for the 2020-2024 contract (extended to 2025 following the COVID pandemic). Indeed, it seemed to us that the unit’s expertise in research questions concerning data, knowledge and constraints could be profitably mobilized to create synergies and be at the origin of original research in explainable AI.
2022 Gilles Audemard, Steve Bellart, Louenas Bounia, Frédéric Koriche, Jean-Marie Lagniez, Pierre Marquis,
On the Explanatory Power of Boolean Decision Trees
in
Data and Knowledge Engineering, vol. 142, pp. 102088, 2022.
2023 Gilles Audemard, Jean-Marie Lagniez, Pierre Marquis, Nicolas Szczepanski,
Computing Abductive Explanations for Boosted Trees
in
26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), vol. 206, 2023.
2023 Ryma Boumazouza, Fahima Cheikh-Alili, Bertrand Mazure, Karim Tabia,
Symbolic Explanations for Multi-Label Classification
in
15th International Conference on Agents and Artificial Intelligence (ICAART 2023), SCITEPRESS - Science and Technology Publications, vol. 3, pp. 342-349, 2023.
2023 Gilles Audemard, Jean-Marie Lagniez, Pierre Marquis, Nicolas Szczepanski,
On Contrastive Explanations for Tree-Based Classifiers
in
The 26th European Conference on Artificial Intelligence (ECAI'23), IOS Press, 2023.
2023 Alexis de Colnet, Pierre Marquis,
On Translations between ML Models for XAI Purposes
in
Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}, International Joint Conferences on Artificial Intelligence Organization, pp. 3158-3166, 2023.
2023 Louenas Bounia, Frederic Koriche,
Approximating Probabilistic Explanations via Supermodular Minimization (Corrected Version)
in
Uncertainty in Artificial Intelligence (UAI 2023)., vol. 216, pp. 216--225, 2023.
2023 Gilles Audemard, Steve Bellart, Jean-Marie Lagniez, Pierre Marquis,
Computing Abductive Explanations for Boosted Regression Trees
in
Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}, International Joint Conferences on Artificial Intelligence Organization, pp. 3432-3441, 2023.
2023 Anthony Blomme, Daniel Le Berre, Anne Parrain, Olivier Roussel,
Compressing UNSAT Search Trees with Caching
in
ICAART 2023 : 15th International Conference on Agents and Artificial Intelligence, vol. 3, pp. 358-365, 2023.
2022 Gilles Audemard, Steve Bellart, Louenas Bounia, Frédéric Koriche, Jean-Marie Lagniez, Pierre Marquis,
Trading Complexity for Sparsity in Random Forest Explanations
in
AAAI Conference on Artificial Intelligence, 2022.
2022 Gilles Audemard, Steve Bellart, Louenas Bounia, Frederic Koriche, Jean-Marie Lagniez, Pierre Marquis,
On Preferred Abductive Explanations for Decision Trees and Random Forests
in
Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}, International Joint Conferences on Artificial Intelligence Organization, pp. 643-650, 2022.
2022 Hakim Radja, Yassine Djouadi, Karim Tabia,
Towards an FCA-Based Approach for Explaining Multi-label Classification
in
Information Processing and Management of Uncertainty in Knowledge-Based Systems - IPMU22, Springer International Publishing, vol. 1602, pp. 638-651, 2022.
2021 Ryma Boumazouza, Fahima Cheikh-Alili, Bertrand Mazure, Karim Tabia,
ASTERYX: A model-Agnostic SaT-basEd appRoach for sYmbolic and score-based eXplanations
in
CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, ACM, pp. 120-129, 2021.
2021 Ryma Boumazouza, Fahima Cheikh-Alili, Bertrand Mazure, Karim Tabia,
A Model-Agnostic SAT-based Approach for Symbolic Explanation Enumeration
in
The 23rd International Conference on Artificial Intelligence (ICAI'21), pp. https://www.springer.com/series/11769, 2021.
2020 Ryma Boumazouza, Fahima Cheikh-Alili, Bertrand Mazure, Karim Tabia,
A Symbolic Approach for Counterfactual Explanations
in
Davis, J., Tabia, K. (eds) Scalable Uncertainty Management (SUM2020), Springer International Publishing, vol. 12322, pp. 270-277, 2020.
2020 Gilles Audemard, Frédéric Koriche, Pierre Marquis,
On Tractable XAI Queries based on Compiled Representations
in
17th International Conference on Principles of Knowledge Representation and Reasoning (KR'20), 2020.
2019 Karim Tabia,
Towards Explainable Multi-Label Classification
in
31st International Conference on Tools with Artificial Intelligence (ICTAI'19), 2019.