Nino Vieillard
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
12
Venues
5
Active years
2020–2025
Best venue rank
A*
Where they publish
Papers
12 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | BOND: Aligning LLMs with Best-of-N Distillation. | Pier Giuseppe Sessa, Robert Dadashi-Tazehozi, Lonard Hussenot, Johan Ferret, Nino Vieillard, Alexandre Ram, Bobak Shahriari, Sarah Perrin, Abram L. Friesen, Geoffrey Cideron, Sertan Girgin, Piotr Stanczyk, Andrea Michi, Danila Sinopalnikov, Sabela Ramos Garea, Amlie Hliou, Aliaksei Severyn, Matthew Hoffman, Nikola Momchev, Olivier Bachem |
| 2025 | ICML | Loss Functions and Operators Generated by f-Divergences. | Vincent Roulet, Tianlin Liu, Nino Vieillard, Michael Eli Sander, Mathieu Blondel |
| 2025 | ICML | On Teacher Hacking in Language Model Distillation. | Daniil Tiapkin, Daniele Calandriello, Johan Ferret, Sarah Perrin, Nino Vieillard, Alexandre Ram, Mathieu Blondel |
| 2024 | ICLR | 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 |
| 2024 | ICML | WARM: On the Benefits of Weight Averaged Reward Models. | Alexandre Ram, Nino Vieillard, Lonard Hussenot, Robert Dadashi, Geoffrey Cideron, Olivier Bachem, Johan Ferret |
| 2023 | ACL | 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, Lonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos Garea, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor |
| 2023 | ICML | 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 Mnard, Mohammad Gheshlaghi Azar, Rmi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvri, Wataru Kumagai, Yutaka Matsuo |
| 2022 | AAAI | Offline Reinforcement Learning as Anti-exploration. | Shideh Rezaeifar, Robert Dadashi, Nino Vieillard, Lonard Hussenot, Olivier Bachem, Olivier Pietquin, Matthieu Geist |
| 2022 | AISTATS | Implicitly Regularized RL with Implicit Q-values. | Nino Vieillard, Marcin Andrychowicz, Anton Raichuk, Olivier Pietquin, Matthieu Geist |
| 2021 | ICML | Offline Reinforcement Learning with Pseudometric Learning. | Robert Dadashi, Shideh Rezaeifar, Nino Vieillard, Lonard Hussenot, Olivier Pietquin, Matthieu Geist |
| 2020 | AAAI | Deep Conservative Policy Iteration. | Nino Vieillard, Olivier Pietquin, Matthieu Geist |
| 2020 | AISTATS | Momentum in Reinforcement Learning. | Nino Vieillard, Bruno Scherrer, Olivier Pietquin, Matthieu Geist |