M2CAI Workflow Challenge: Convolutional Neural Networks with Time Smoothing and Hidden Markov Model for Video Frames Classification. - Rémi Cadène; Thomas Robert 001; Nicolas Thome; Matthieu Cord (CoRR, 2016)

Master's Thesis : Deep Learning for Visual Recognition. - Rémi Cadène; Nicolas Thome; Matthieu Cord (CoRR, 2016)

MUTAN: Multimodal Tucker Fusion for Visual Question Answering. - Hédi Ben-Younes; Rémi Cadène; Matthieu Cord; Nicolas Thome (ICCV, 2017)

Images and Recipes: Retrieval in the Cooking Context. - Micael Carvalho; Rémi Cadène; David Picard; Laure Soulier; Matthieu Cord (ICDE Workshops, 2018)

Cross-Modal Retrieval in the Cooking Context: Learning Semantic Text-Image Embeddings. - Micael Carvalho; Rémi Cadène; David Picard; Laure Soulier; Nicolas Thome; Matthieu Cord (SIGIR, 2018)

Benchmark Analysis of Representative Deep Neural Network Architectures. - Simone Bianco 001; Rémi Cadène; Luigi Celona; Paolo Napoletano (IEEE Access, 2018)

Images & Recipes: Retrieval in the cooking context. - Micael Carvalho; Rémi Cadène; David Picard; Laure Soulier; Matthieu Cord (CoRR, 2018)

BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection. - Hédi Ben-Younes; Rémi Cadène; Nicolas Thome; Matthieu Cord (AAAI, 2019)

MUREL: Multimodal Relational Reasoning for Visual Question Answering. - Rémi Cadène; Hédi Ben-Younes; Matthieu Cord; Nicolas Thome (CVPR, 2019)

RUBi: Reducing Unimodal Biases for Visual Question Answering. - Rémi Cadène; Corentin Dancette; Hédi Ben-Younes; Matthieu Cord; Devi Parikh (NeurIPS, 2019)

Overcoming Statistical Shortcuts for Open-ended Visual Counting. - Corentin Dancette; Rémi Cadène; Xinlei Chen; Matthieu Cord (CoRR, 2020)

Deep Multimodal Learning for Vision and Language Processing. (Apprentissage Multimodal Profond pour le Traitement de la Vision et du Langage). - Rémi Cadène (2020)

Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering. - Corentin Dancette; Rémi Cadène; Damien Teney; Matthieu Cord (ICCV, 2021)

Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis. - Thomas Fel; Rémi Cadène; Mathieu Chalvidal; Matthieu Cord; David Vigouroux; Thomas Serre (NeurIPS, 2021)

What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods. - Julien Colin; Thomas Fel; Rémi Cadène; Thomas Serre (NeurIPS, 2022)

How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural Networks. - Thomas Fel; David Vigouroux; Rémi Cadène; Thomas Serre (WACV, 2022)

Xplique: A Deep Learning Explainability Toolbox. - Thomas Fel; Lucas Hervier; David Vigouroux; Antonin Poché; Justin Plakoo; Rémi Cadène; Mathieu Chalvidal; Julien Colin; Thibaut Boissin; Louis Béthune; Agustin Martin Picard; Claire Nicodeme; et al. (CoRR, 2022)

Understanding the Computational Demands Underlying Visual Reasoning. - Mohit Vaishnav; Rémi Cadène; Andrea Alamia; Drew Linsley; Rufin VanRullen; Thomas Serre (Neural Comput., 2022)

Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis. - Thomas Fel; Melanie Ducoffe; David Vigouroux; Rémi Cadène; Mikael Capelle; Claire Nicodème; Thomas Serre (CVPR, 2023)

CRAFT: Concept Recursive Activation FacTorization for Explainability. - Thomas Fel; Agustin Martin Picard; Louis Béthune; Thibaut Boissin; David Vigouroux; Julien Colin; Rémi Cadène; Thomas Serre (CVPR, 2023)

A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation. - Thomas Fel; Victor Boutin; Louis Béthune; Rémi Cadène; Mazda Moayeri; Léo Andéol; Mathieu Chalvidal; Thomas Serre (NeurIPS, 2023)

Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization. - Thomas Fel; Thibaut Boissin; Victor Boutin; Agustin Picard; Paul Novello; Julien Colin; Drew Linsley; Tom Rousseau; Rémi Cadène; Lore Goetschalckx; Laurent Gardes; Thomas Serre (NeurIPS, 2023)

Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization. - Thomas Fel; Thibaut Boissin; Victor Boutin; Agustin Martin Picard; Paul Novello; Julien Colin; Drew Linsley; Tom Rousseau; Rémi Cadène; Laurent Gardes; Thomas Serre (CoRR, 2023)

SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics. - Mustafa Shukor; Dana Aubakirova; Francesco Capuano; Pepijn Kooijmans; Steven Palma; Adil Zouitine; Michel Aractingi; Caroline Pascal; Martino Russi; Andrés Marafioti; Simon Alibert; Matthieu Cord; et al. (CoRR, 2025)