An objective function for STDP. - Yoshua Bengio; Thomas Mesnard; Asja Fischer; Saizheng Zhang; Yuhai Wu (CoRR, 2015)

Towards deep learning with spiking neurons in energy based models with contrastive Hebbian plasticity. - Thomas Mesnard; Wulfram Gerstner; Johanni Brea (CoRR, 2016)

STDP-Compatible Approximation of Backpropagation in an Energy-Based Model. - Yoshua Bengio; Thomas Mesnard; Asja Fischer; Saizheng Zhang; Yuhuai Wu (Neural Comput., 2017)

Extending the Framework of Equilibrium Propagation to General Dynamics. - Benjamin Scellier; Anirudh Goyal; Jonathan Binas; Thomas Mesnard; Yoshua Bengio (ICLR (Workshop), 2018)

Generalization of Equilibrium Propagation to Vector Field Dynamics. - Benjamin Scellier; Anirudh Goyal; Jonathan Binas; Thomas Mesnard; Yoshua Bengio (CoRR, 2018)

Hindsight Credit Assignment. - Anna Harutyunyan; Will Dabney; Thomas Mesnard; Mohammad Gheshlaghi Azar; Bilal Piot; Nicolas Heess; Hado van Hasselt; Gregory Wayne; Satinder Singh 001; Doina Precup; Rémi Munos (NeurIPS, 2019)

Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks. - Thomas Mesnard; Gaëtan Vignoud; João Sacramento; Walter Senn; Yoshua Bengio (CoRR, 2019)

Counterfactual Credit Assignment in Model-Free Reinforcement Learning. - Thomas Mesnard; Théophane Weber; Fabio Viola; Shantanu Thakoor; Alaa Saade; Anna Harutyunyan; Will Dabney; Tom Stepleton; Nicolas Heess; Arthur Guez; Marcus Hutter; Lars Buesing; et al. (CoRR, 2020)

Counterfactual Credit Assignment in Model-Free Reinforcement Learning. - Thomas Mesnard; Theophane Weber; Fabio Viola; Shantanu Thakoor; Alaa Saade; Anna Harutyunyan; Will Dabney; Thomas S. Stepleton; Nicolas Heess; Arthur Guez; Eric Moulines; Marcus Hutter; et al. (ICML, 2021)

Geometric Entropic Exploration. - Zhaohan Daniel Guo; Mohammad Gheshlaghi Azar; Alaa Saade; Shantanu Thakoor; Bilal Piot; Bernardo Ávila Pires; Michal Valko; Thomas Mesnard; Tor Lattimore; Rémi Munos (CoRR, 2021)

Curiosity in hindsight. - Daniel Jarrett; Corentin Tallec; Florent Altché; Thomas Mesnard; Rémi Munos; Michal Valko (CoRR, 2022)

Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments. - Daniel Jarrett; Corentin Tallec; Florent Altché; Thomas Mesnard; Rémi Munos; Michal Valko (ICML, 2023)

Quantile Credit Assignment. - Thomas Mesnard; Wenqi Chen; Alaa Saade; Yunhao Tang; Mark Rowland 001; Theophane Weber; Clare Lyle; Audrunas Gruslys; Michal Valko; Will Dabney; Georg Ostrovski; Eric Moulines; et al. (ICML, 2023)

RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback. - Harrison Lee 001; Samrat Phatale; Hassan Mansoor; Kellie Lu; Thomas Mesnard; Colton Bishop; Victor Carbune; Abhinav Rastogi (CoRR, 2023)

Nash Learning from Human Feedback. - Rémi Munos; Michal Valko; Daniele Calandriello; Mohammad Gheshlaghi Azar; Mark Rowland 001; Zhaohan Daniel Guo; Yunhao Tang; Matthieu Geist; Thomas Mesnard; Andrea Michi; Marco Selvi; Sertan Girgin; et al. (CoRR, 2023)

Credit Assignment in Deep Reinforcement Learning. (Attribution de crédit pour l'apprentissage par renforcement dans des réseaux profonds). - Thomas Mesnard (2023)

RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback. - Harrison Lee 001; Samrat Phatale; Hassan Mansoor; Thomas Mesnard; Johan Ferret; Kellie Lu; Colton Bishop; Ethan Hall; Victor Carbune; Abhinav Rastogi; Sushant Prakash (ICML, 2024)

Nash Learning from Human Feedback. - Rémi Munos; Michal Valko; Daniele Calandriello; Mohammad Gheshlaghi Azar; Mark Rowland 001; Daniel Guo 001; Yunhao Tang; Matthieu Geist; Thomas Mesnard; Côme Fiegel; Andrea Michi; Marco Selvi; et al. (ICML, 2024)

Direct Language Model Alignment from Online AI Feedback. - Shangmin Guo; Biao Zhang; Tianlin Liu; Tianqi Liu 002; Misha Khalman; Felipe Llinares; Alexandre Ramé; Thomas Mesnard; Yao Zhao; Bilal Piot; Johan Ferret; Mathieu Blondel (CoRR, 2024)

Gemma: Open Models Based on Gemini Research and Technology. - Thomas Mesnard; Cassidy Hardin; Robert Dadashi; Surya Bhupatiraju; Shreya Pathak; Laurent Sifre; Morgane Rivière; Mihir Sanjay Kale; Juliette Love; Pouya Tafti; Léonard Hussenot; Aakanksha Chowdhery; et al. (CoRR, 2024)

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. - Aleksandar Botev; Soham De; Samuel L. Smith; Anushan Fernando; George-Cristian Muraru; Ruba Haroun; Leonard Berrada; Razvan Pascanu; Pier Giuseppe Sessa; Robert Dadashi; Léonard Hussenot; Johan Ferret; et al. (CoRR, 2024)

Gemma 2: Improving Open Language Models at a Practical Size. - Morgane Rivière; Shreya Pathak; Pier Giuseppe Sessa; Cassidy Hardin; Surya Bhupatiraju; Léonard Hussenot; Thomas Mesnard; Bobak Shahriari; Alexandre Ramé; Johan Ferret; Peter Liu; Pouya Tafti; et al. (CoRR, 2024)

PaliGemma 2: A Family of Versatile VLMs for Transfer. - Andreas Steiner 001; André Susano Pinto; Michael Tschannen; Daniel Keysers; Xiao Wang 038; Yonatan Bitton; Alexey A. Gritsenko; Matthias Minderer; Anthony Sherbondy; Shangbang Long; Siyang Qin; R. Reeve Ingle; et al. (CoRR, 2024)

A Survey of Temporal Credit Assignment in Deep Reinforcement Learning. - Eduardo Pignatelli; Johan Ferret; Matthieu Geist; Thomas Mesnard; Hado van Hasselt; Laura Toni (Trans. Mach. Learn. Res., 2024)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)

MedGemma Technical Report. - Andrew Sellergren; Sahar Kazemzadeh; Tiam Jaroensri; Atilla P. Kiraly; Madeleine Traverse; Timo Kohlberger; Shawn Xu; Fayaz Jamil; Cían Hughes; Charles Lau; Justin Chen; Fereshteh Mahvar; et al. (CoRR, 2025)