Hussenot, Leonard

13 publications

ICLR 2025 BOND: Aligning LLMs with Best-of-N Distillation Pier Giuseppe Sessa, Robert Dadashi-Tazehozi, Leonard Hussenot, Johan Ferret, Nino Vieillard, Alexandre Rame, Bobak Shahriari, Sarah Perrin, Abram L. Friesen, Geoffrey Cideron, Sertan Girgin, Piotr Stanczyk, Andrea Michi, Danila Sinopalnikov, Sabela Ramos Garea, Amélie Héliou, Aliaksei Severyn, Matthew Hoffman, Nikola Momchev, Olivier Bachem

NeurIPSW 2024 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, Kumar Avinava Dubey, Alexandre Rame, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Leonard Hussenot, Olivier Bachem, Edouard Leurent

ICML 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, Leonard Hussenot, Neil Zeghidour, Andrea Agostinelli

ICML 2024 WARM: On the Benefits of Weight Averaged Reward Models Alexandre Rame, Nino Vieillard, Leonard Hussenot, Robert Dadashi-Tazehozi, Geoffrey Cideron, Olivier Bachem, Johan Ferret

ICML 2022 Continuous Control with Action Quantization from Demonstrations Robert Dadashi, Léonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin

NeurIPS 2022 Learning Energy Networks with Generalized Fenchel-Young Losses Mathieu Blondel, Felipe Llinares-Lopez, Robert Dadashi, Leonard Hussenot, Matthieu Geist

AAAI 2022 Offline Reinforcement Learning as Anti-Exploration Shideh Rezaeifar, Robert Dadashi, Nino Vieillard, Léonard Hussenot, Olivier Bachem, Olivier Pietquin, Matthieu Geist

NeurIPSW 2021 Continuous Control with Action Quantization from Demonstrations Robert Dadashi, Leonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin

ICML 2021 Hyperparameter Selection for Imitation Learning Léonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphael Marinier, Lukasz Stafiniak, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin

ICML 2021 Offline Reinforcement Learning with Pseudometric Learning Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Léonard Hussenot, Olivier Pietquin, Matthieu Geist

ICLR 2021 Primal Wasserstein Imitation Learning Robert Dadashi, Leonard Hussenot, Matthieu Geist, Olivier Pietquin

NeurIPS 2021 What Matters for Adversarial Imitation Learning? Manu Orsini, Anton Raichuk, Leonard Hussenot, Damien Vincent, Robert Dadashi, Sertan Girgin, Matthieu Geist, Olivier Bachem, Olivier Pietquin, Marcin Andrychowicz

ICLR 2021 What Matters for On-Policy Deep Actor-Critic Methods? a Large-Scale Study Marcin Andrychowicz, Anton Raichuk, Piotr Stańczyk, Manu Orsini, Sertan Girgin, Raphaël Marinier, Leonard Hussenot, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem