Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications. - Sarah Perrin; Julien Pérolat; Mathieu Laurière; Matthieu Geist; Romuald Elie; Olivier Pietquin (NeurIPS, 2020)

Mean Field Games Flock! The Reinforcement Learning Way. - Sarah Perrin; Mathieu Laurière; Julien Pérolat; Matthieu Geist; Romuald Élie; Olivier Pietquin (IJCAI, 2021)

Scaling up Mean Field Games with Online Mirror Descent. - Julien Pérolat; Sarah Perrin; Romuald Elie; Mathieu Laurière; Georgios Piliouras; Matthieu Geist; Karl Tuyls; Olivier Pietquin (CoRR, 2021)

Generalization in Mean Field Games by Learning Master Policies. - Sarah Perrin; Mathieu Laurière; Julien Pérolat; Romuald Élie; Matthieu Geist; Olivier Pietquin (AAAI, 2022)

Solving N-Player Dynamic Routing Games with Congestion: A Mean-Field Approach. - Theophile Cabannes; Mathieu Laurière; Julien Pérolat; Raphaël Marinier; Sertan Girgin; Sarah Perrin; Olivier Pietquin; Alexandre M. Bayen; Eric Goubault; Romuald Elie (AAMAS, 2022)

Concave Utility Reinforcement Learning: The Mean-field Game Viewpoint. - Matthieu Geist; Julien Pérolat; Mathieu Laurière; Romuald Elie; Sarah Perrin; Olivier Bachem; Rémi Munos; Olivier Pietquin (AAMAS, 2022)

Scaling Mean Field Games by Online Mirror Descent. - Julien Pérolat; Sarah Perrin; Romuald Elie; Mathieu Laurière; Georgios Piliouras; Matthieu Geist; Karl Tuyls; Olivier Pietquin (AAMAS, 2022)

Scalable Deep Reinforcement Learning Algorithms for Mean Field Games. - Mathieu Laurière; Sarah Perrin; Sertan Girgin; Paul Muller; Ayush Jain; Theophile Cabannes; Georgios Piliouras; Julien Pérolat; Romuald Elie; Olivier Pietquin; Matthieu Geist (ICML, 2022)

Learning Mean Field Games: A Survey. - Mathieu Laurière; Sarah Perrin; Matthieu Geist; Olivier Pietquin (CoRR, 2022)

Learning Correlated Equilibria in Mean-Field Games. - Paul Muller; Romuald Elie; Mark Rowland 001; Mathieu Laurière; Julien Pérolat; Sarah Perrin; Matthieu Geist; Georgios Piliouras; Olivier Pietquin; Karl Tuyls (CoRR, 2022)

Scaling up Multi-agent Reinforcement Learning with Mean Field Games and Vice-versa. (Mise à l'échelle de l'apprentissage par renforcement multi-agent grâce aux jeux à champ moyen et vice-versa). - Sarah Perrin (2022)

Approximating the Core via Iterative Coalition Sampling. - Ian Gemp; Marc Lanctot; Luke Marris; Yiran Mao; Edgar A. Duéñez-Guzmán; Sarah Perrin; András György 001; Romuald Elie; Georgios Piliouras; Michael Kaisers; Daniel Hennes; Kalesha Bullard; et al. (AAMAS, 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)

Mastering Board Games by External and Internal Planning with Language Models. - John Schultz; Jakub Adámek; Matej Jusup; Marc Lanctot; Michael Kaisers; Sarah Perrin; Daniel Hennes; Jeremy Shar; Cannada Lewis; Anian Ruoss; Tom Zahavy; Petar Velickovic; et al. (CoRR, 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)