Towards Explainable Neural-Symbolic Visual Reasoning. - Adrien Bennetot; Jean-Luc Laurent; Raja Chatila 001; Natalia Díaz Rodríguez (NeSy@IJCAI, 2019)

Highlighting Bias with Explainable Neural-Symbolic Visual Reasoning. - Adrien Bennetot; Jean-Luc Laurent; Raja Chatila 001; Natalia Díaz Rodríguez (CoRR, 2019)

Should artificial agents ask for help in human-robot collaborative problem-solving? - Adrien Bennetot; Vicky Charisi; Natalia Díaz Rodríguez (CoRR, 2020)

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. - Alejandro Barredo Arrieta; Natalia Díaz Rodríguez; Javier Del Ser; Adrien Bennetot; Siham Tabik; Alberto Barbado; Salvador García 001; Sergio Gil-Lopez; Daniel Molina; Richard Benjamins; Raja Chatila 001; Francisco Herrera (Inf. Fusion, 2020)

Greybox XAI: A Neural-Symbolic learning framework to produce interpretable predictions for image classification. - Adrien Bennetot; Gianni Franchi; Javier Del Ser; Raja Chatila 001; Natalia Díaz Rodríguez (Knowl. Based Syst., 2022)

Explaining Aha! moments in artificial agents through IKE-XAI: Implicit Knowledge Extraction for eXplainable AI. - Ikram Chraibi Kaadoud; Adrien Bennetot; Barbara Mawhin; Vicky Charisi; Natalia Díaz Rodríguez (Neural Networks, 2022)

A Neural-Symbolic learning framework to produce interpretable predictions for image classification. (Modèle d'apprentissage neuro-symbolique pour produire des prédictions interprétables pour de la classification d'imagines). - Adrien Bennetot (2022)

T-Rep: Representation Learning for Time Series using Time-Embeddings. - Archibald Fraikin; Adrien Bennetot; Stéphanie Allassonnière (ICLR, 2024)

A Practical Tutorial on Explainable AI Techniques. - Adrien Bennetot; Ivan Donadello; Ayoub El Qadi; Mauro Dragoni; Thomas Frossard; Benedikt Wagner; Anna Saranti; Silvia Tulli; Maria Trocan; Raja Chatila 001; Andreas Holzinger; Artur d'Avila Garcez; et al. (ACM Comput. Surv., 2025)