The Description Length of Deep Learning models. - Léonard Blier; Yann Ollivier (NeurIPS, 2018)

Do Deep Learning Models Have Too Many Parameters? An Information Theory Viewpoint. - Léonard Blier; Yann Ollivier (CoRR, 2018)

Making Deep Q-learning methods robust to time discretization. - Corentin Tallec; Léonard Blier; Yann Ollivier (ICML, 2019)

Learning with Random Learning Rates. - Léonard Blier; Pierre Wolinski; Yann Ollivier (ECML/PKDD (2), 2019)

Learning Successor States and Goal-Dependent Values: A Mathematical Viewpoint. - Léonard Blier; Corentin Tallec; Yann Ollivier (CoRR, 2021)

Unbiased Methods for Multi-Goal Reinforcement Learning. - Léonard Blier; Yann Ollivier (CoRR, 2021)

Sur certaines méthodes raisonnées pour l'apprentissage par renforcement profond. (Some Principled Methods for Deep Reinforcement Learning). - Léonard Blier (2022)

Magistral. - Abhinav Rastogi; Albert Q. Jiang; Andy Lo; Gabrielle Berrada; Guillaume Lample; Jason Rute; Joep Barmentlo; Karmesh Yadav; Kartik Khandelwal; Khyathi Raghavi Chandu; Léonard Blier; Lucile Saulnier; et al. (CoRR, 2025)

Voxtral. - Alexander H. Liu; Andy Ehrenberg; Andy Lo; Clément Denoix; Corentin Barreau; Guillaume Lample; Jean-Malo Delignon; Khyathi Raghavi Chandu; Patrick von Platen; Pavankumar Reddy Muddireddy; Sanchit Gandhi; Soham Ghosh; et al. (CoRR, 2025)