Nino Vieillard

According to our database, Nino Vieillard authored at least 21 papers between 2019 and 2025.

Collaborative distances:

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

2025

On Teacher Hacking in Language Model Distillation.

Daniil Tiapkin, Daniele Calandriello, Johan Ferret, Sarah Perrin, Nino Vieillard, Alexandre Ramé, Mathieu Blondel

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Loss Functions and Operators Generated by f-Divergences.

Vincent Roulet, Tianlin Liu, Nino Vieillard, Michael Eli Sander, Mathieu Blondel

Proceedings of the Forty-second International Conference on Machine Learning, 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, Andrea Michi, Danila Sinopalnikov, Sabela Ramos Garea, Amélie Héliou, Aliaksei Severyn, Matthew Hoffman, Nikola Momchev, Olivier Bachem

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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, Andrea Michi, Danila Sinopalnikov, Sabela Ramos, Amélie Héliou, Aliaksei Severyn, Matt Hoffman, Nikola Momchev, Olivier Bachem

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

Imitating Language via Scalable Inverse Reinforcement Learning.

Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jörg Bornschein, Sandy H. Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin A. Riedmiller

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

WARM: On the Benefits of Weight Averaged Reward Models.

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes.

Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, Piotr Stanczyk, Sabela Ramos Garea, Matthieu Geist, Olivier Bachem

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

GKD: Generalized Knowledge Distillation for Auto-regressive Sequence Models.

Rishabh Agarwal, Nino Vieillard, Piotr Stanczyk, Sabela Ramos, Matthieu Geist, Olivier Bachem

CoRR, 2023

Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice.

Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Rémi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvári, Wataru Kumagai, Yutaka Matsuo

Proceedings of the International Conference on Machine Learning, 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

KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal.

Tadashi Kozuno, Wenhao Yang, Nino Vieillard, Toshinori Kitamura, Yunhao Tang, Jincheng Mei, Pierre Ménard, Mohammad Gheshlaghi Azar, Michal Valko, Rémi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvári

CoRR, 2022

Implicitly Regularized RL with Implicit Q-values.

Nino Vieillard, Marcin Andrychowicz, Anton Raichuk, Olivier Pietquin, Matthieu Geist

Proceedings of the International Conference on Artificial Intelligence and Statistics, 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

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

2020

Leverage the Average: an Analysis of Regularization in RL.

Nino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist

CoRR, 2020

Munchausen Reinforcement Learning.

Nino Vieillard, Olivier Pietquin, Matthieu Geist

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning.

Nino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Momentum in Reinforcement Learning.

Nino Vieillard, Bruno Scherrer, Olivier Pietquin, Matthieu Geist

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Deep Conservative Policy Iteration.

Nino Vieillard, Olivier Pietquin, Matthieu Geist

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

On Connections between Constrained Optimization and Reinforcement Learning.

Nino Vieillard, Olivier Pietquin, Matthieu Geist

CoRR, 2019