Léonard Hussenot

According to our database, Léonard Hussenot authored at least 20 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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, Adam Roberts, Aditya Barua, Alex Botev, Alex Castro-Ros, Ambrose Slone, Amélie Héliou, Andrea Tacchetti, Anna Bulanova, Antonia Paterson, Beth Tsai, Bobak Shahriari, Charline Le Lan, Christopher A. Choquette-Choo, Clément Crepy, Daniel Cer, Daphne Ippolito, David Reid, Elena Buchatskaya, Eric Ni, Eric Noland, Geng Yan, George Tucker, George-Christian Muraru, Grigory Rozhdestvenskiy, Henryk Michalewski, Ian Tenney, Ivan Grishchenko, Jacob Austin, James Keeling, Jane Labanowski, Jean-Baptiste Lespiau, Jeff Stanway, Jenny Brennan, Jeremy Chen, Johan Ferret, Justin Chiu, et al.

CoRR, 2024

MusicRL: Aligning Music Generation to Human Preferences.

Geoffrey Cideron, Sertan Girgin, Mauro Verzetti, Damien Vincent, Matej Kastelic, Zalán Borsos, Brian McWilliams, Victor Ungureanu, Olivier Bachem, Olivier Pietquin, Matthieu Geist, Léonard Hussenot, Neil Zeghidour, Andrea Agostinelli

CoRR, 2024

WARM: On the Benefits of Weight Averaged Reward Models.

Alexandre Ramé, Nino Vieillard, Léonard Hussenot, Robert Dadashi, Geoffrey Cideron, Olivier Bachem, Johan Ferret

CoRR, 2024

2023

Get Back Here: Robust Imitation by Return-to-Distribution Planning.

Geoffrey Cideron, Baruch Tabanpour, Sebastian Curi, Sertan Girgin, Léonard Hussenot, Gabriel Dulac-Arnold, Matthieu Geist, Olivier Pietquin, Robert Dadashi

CoRR, 2023

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, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Apprentissage par démonstrations : transfert des motivations humaines aux algorithmes. (Apprenticeship learning : transferring human motivations to artificial agents).

Léonard Hussenot

PhD thesis, 2022

vec2text with Round-Trip Translations.

Geoffrey Cideron, Sertan Girgin, Anton Raichuk, Olivier Pietquin, Olivier Bachem, Léonard Hussenot

CoRR, 2022

Learning Energy Networks with Generalized Fenchel-Young Losses.

Mathieu Blondel, Felipe Llinares-López, Robert Dadashi, Léonard Hussenot, Matthieu Geist

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Continuous Control with Action Quantization from Demonstrations.

Robert Dadashi, Léonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin

Proceedings of the International Conference on Machine Learning, 2022

Offline Reinforcement Learning as Anti-exploration.

Shideh Rezaeifar, Robert Dadashi, Nino Vieillard, Léonard Hussenot, Olivier Bachem, Olivier Pietquin, Matthieu Geist

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning.

Sabela Ramos, Sertan Girgin, Léonard Hussenot, Damien Vincent, Hanna Yakubovich, Daniel Toyama, Anita Gergely, Piotr Stanczyk, Raphaël Marinier, Jeremiah Harmsen, Olivier Pietquin, Nikola Momchev

CoRR, 2021

What Matters for Adversarial Imitation Learning?

Manu Orsini, Anton Raichuk, Léonard Hussenot, Damien Vincent, Robert Dadashi, Sertan Girgin, Matthieu Geist, Olivier Bachem, Olivier Pietquin, Marcin Andrychowicz

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Hyperparameter Selection for Imitation Learning.

Léonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphaël Marinier, Lukasz Stafiniak, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin

Proceedings of the 38th International Conference on Machine Learning, 2021

Offline Reinforcement Learning with Pseudometric Learning.

Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, Matthieu Geist

Proceedings of the 38th International Conference on Machine Learning, 2021

Primal Wasserstein Imitation Learning.

Robert Dadashi, Léonard Hussenot, Matthieu Geist, Olivier Pietquin

Proceedings of the 9th International Conference on Learning Representations, 2021

What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study.

Marcin Andrychowicz, Anton Raichuk, Piotr Stanczyk, Manu Orsini, Sertan Girgin, Raphaël Marinier, Léonard Hussenot, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem

Proceedings of the 9th International Conference on Learning Representations, 2021

Show Me the Way: Intrinsic Motivation from Demonstrations.

Léonard Hussenot, Robert Dadashi, Matthieu Geist, Olivier Pietquin

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study.

Marcin Andrychowicz, Anton Raichuk, Piotr Stanczyk, Manu Orsini, Sertan Girgin, Raphaël Marinier, Léonard Hussenot, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem

CoRR, 2020

CopyCAT: : Taking Control of Neural Policies with Constant Attacks.

Léonard Hussenot, Matthieu Geist, Olivier Pietquin

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Targeted Attacks on Deep Reinforcement Learning Agents through Adversarial Observations.

Léonard Hussenot, Matthieu Geist, Olivier Pietquin

CoRR, 2019