Perfect Matching for Biconnected Cubic Graphs in O(n log2n) Time. - Krzysztof Diks; Piotr Stanczyk (SOFSEM, 2010)

Google Research Football: A Novel Reinforcement Learning Environment. - Karol Kurach; Anton Raichuk; Piotr Stanczyk; Michal Zajac 005; Olivier Bachem; Lasse Espeholt; Carlos Riquelme; Damien Vincent; Marcin Michalski; Olivier Bousquet; Sylvain Gelly (AAAI, 2020)

SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. - Lasse Espeholt; Raphaël Marinier; Piotr Stanczyk; Ke Wang; Marcin Michalski (ICLR, 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)

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 (ICLR, 2021)

Launchpad: A Programming Model for Distributed Machine Learning Research. - Fan Yang; Gabriel Barth-Maron; Piotr Stanczyk; Matthew W. Hoffman; Siqi Liu 002; Manuel Kroiss; Aedan Pope; Alban Rrustemi (CoRR, 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)

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; et al. (ACL (1), 2023)

GKD: Generalized Knowledge Distillation for Auto-regressive Sequence Models. - Rishabh Agarwal; Nino Vieillard; Piotr Stanczyk; Sabela Ramos; Matthieu Geist; Olivier Bachem (CoRR, 2023)

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 (ICLR, 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)

Gemma 2: Improving Open Language Models at a Practical Size. - Morgane Rivière; Shreya Pathak; Pier Giuseppe Sessa; Cassidy Hardin; Surya Bhupatiraju; Léonard Hussenot; Thomas Mesnard; Bobak Shahriari; Alexandre Ramé; Johan Ferret; Peter Liu; Pouya Tafti; et al. (CoRR, 2024)

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)