Credit Assignment as a Proxy for Transfer in Reinforcement Learning. - Johan Ferret; Raphaël Marinier; Matthieu Geist; Olivier Pietquin (CoRR, 2019)

Self-Attentional Credit Assignment for Transfer in Reinforcement Learning. - Johan Ferret; Raphaël Marinier; Matthieu Geist; Olivier Pietquin (IJCAI, 2020)

Self-Imitation Advantage Learning. - Johan Ferret; Olivier Pietquin; Matthieu Geist (AAMAS, 2021)

Adversarially Guided Actor-Critic. - Yannis Flet-Berliac; Johan Ferret; Olivier Pietquin; Philippe Preux; Matthieu Geist (ICLR, 2021)

There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning. - Nathan Grinsztajn; Johan Ferret; Olivier Pietquin; Philippe Preux; Matthieu Geist (NeurIPS, 2021)

More Efficient Exploration with Symbolic Priors on Action Sequence Equivalences. - Toby Johnstone; Nathan Grinsztajn; Johan Ferret; Philippe Preux (CoRR, 2021)

Lazy-MDPs: Towards Interpretable RL by Learning When to Act. - Alexis Jacq; Johan Ferret; Olivier Pietquin; Matthieu Geist (AAMAS, 2022)

Lazy-MDPs: Towards Interpretable Reinforcement Learning by Learning When to Act. - Alexis Jacq; Johan Ferret; Olivier Pietquin; Matthieu Geist (CoRR, 2022)

On actions that matter: credit assignment and interpretability in reinforcement learning. (De l'importance des actions: assignation de crédit et interprétabilité pour l'apprentissage par renforcement). - Johan Ferret (2022)

Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. - Paul Roit; Johan Ferret; Lior Shani; Roee Aharoni; Geoffrey Cideron; Robert Dadashi; Matthieu Geist; Sertan Girgin; Léonard Hussenot; Orgad Keller; Nikola Momchev; Sabela Ramos Garea; et al. (ACL (1), 2023)

Conditional Language Policy: A General Framework For Steerable Multi-Objective Finetuning. - Kaiwen Wang; Rahul Kidambi; Ryan Sullivan; Alekh Agarwal; Christoph Dann; Andrea Michi; Marco Gelmi; Yunxuan Li; Raghav Gupta; Avinava Dubey; Alexandre Ramé; Johan Ferret; et al. (EMNLP (Findings), 2024)

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)

WARM: On the Benefits of Weight Averaged Reward Models. - Alexandre Ramé; Nino Vieillard; Léonard Hussenot; Robert Dadashi; Geoffrey Cideron; Olivier Bachem; Johan Ferret (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)

WARP: On the Benefits of Weight Averaged Rewarded Policies. - Alexandre Ramé; Johan Ferret; Nino Vieillard; Robert Dadashi; Léonard Hussenot; Pierre-Louis Cedoz; Pier Giuseppe Sessa; Sertan Girgin; Arthur Douillard; Olivier Bachem (CoRR, 2024)

BOND: Aligning LLMs with Best-of-N Distillation. - Pier Giuseppe Sessa; Robert Dadashi; Léonard Hussenot; Johan Ferret; Nino Vieillard; Alexandre Ramé; Bobak Shahriari; Sarah Perrin; Abe Friesen; Geoffrey Cideron; Sertan Girgin; Piotr Stanczyk; et al. (CoRR, 2024)

Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning. - Kaiwen Wang; Rahul Kidambi; Ryan Sullivan; Alekh Agarwal; Christoph Dann; Andrea Michi; Marco Gelmi; Yunxuan Li; Raghav Gupta; Avinava Dubey; Alexandre Ramé; 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)

Assessing the Zero-Shot Capabilities of LLMs for Action Evaluation in RL. - Eduardo Pignatelli; Johan Ferret; Tim Rocktäschel; Edward Grefenstette; Davide Paglieri; Samuel Coward; Laura Toni (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)

Diversity-Rewarded CFG Distillation. - Geoffrey Cideron; Andrea Agostinelli; Johan Ferret; Sertan Girgin; Romuald Elie; Olivier Bachem; Sarah Perrin; Alexandre Ramé (ICLR, 2025)

BOND: Aligning LLMs with Best-of-N Distillation. - Pier Giuseppe Sessa; Robert Dadashi-Tazehozi; Léonard Hussenot; Johan Ferret; Nino Vieillard; Alexandre Ramé; Bobak Shahriari; Sarah Perrin; Abram L. Friesen; Geoffrey Cideron; Sertan Girgin; Piotr Stanczyk; et al. (ICLR, 2025)

On Teacher Hacking in Language Model Distillation. - Daniil Tiapkin; Daniele Calandriello; Johan Ferret; Sarah Perrin; Nino Vieillard; Alexandre Ramé; Mathieu Blondel (CoRR, 2025)

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)