Grandmaster level in StarCraft II using multi-agent reinforcement learning O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ... Nature 575 (7782), 350-354, 2019 | 4115 | 2019 |
Competition-level code generation with alphacode Y Li, D Choi, J Chung, N Kushman, J Schrittwieser, R Leblond, T Eccles, ... Science 378 (6624), 1092-1097, 2022 | 801* | 2022 |
Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023 | 419 | 2023 |
ASAGA: asynchronous parallel SAGA R Leblond, F Pedregosa, S Lacoste-Julien AISTATS 2017, 2016 | 137 | 2016 |
Improved asynchronous parallel optimization analysis for stochastic incremental methods R Leblond, F Pedregosa, S Lacoste-Julien JMLR, 2018 | 73 | 2018 |
Machine Translation Decoding beyond Beam Search R Leblond, JB Alayrac, L Sifre, M Pislar, JB Lespiau, I Antonoglou, ... EMNLP 2021, 2021 | 60 | 2021 |
Continuous diffusion for categorical data S Dieleman, L Sartran, A Roshannai, N Savinov, Y Ganin, PH Richemond, ... arXiv preprint arXiv:2211.15089, 2022 | 54 | 2022 |
SEARNN: Training RNNs with global-local losses R Leblond, JB Alayrac, A Osokin, S Lacoste-Julien ICLR 2018, 2017 | 51 | 2017 |
Breaking the nonsmooth barrier: A scalable parallel method for composite optimization F Pedregosa, R Leblond, S Lacoste-Julien Advances in Neural Information Processing Systems 30, 2017 | 48 | 2017 |
OPtions as REsponses: Grounding Behavioural Hierarchies in Multi-Agent Reinforcement Learning A Vezhnevets, Y Wu, M Eckstein, R Leblond, JZ Leibo ICML, 2020 | 29 | 2020 |
Options as responses: Grounding behavioural hierarchies in multi-agent RL AS Vezhnevets, Y Wu, R Leblond, JZ Leibo arXiv preprint arXiv:1906.01470, 2019 | 20 | 2019 |
Self-conditioned embedding diffusion for text generation R Strudel, C Tallec, F Altché, Y Du, Y Ganin, A Mensch, W Grathwohl, ... arXiv preprint arXiv:2211.04236, 2022 | 19 | 2022 |
Cutoff phenomenon for the simple exclusion process on the complete graph H Lacoin, R Leblond ALEA 2011, 2010 | 18 | 2010 |
Asynchronous optimization for machine learning R Leblond Paris Sciences et Lettres (ComUE), 2018 | 2 | 2018 |
Discrete token processing using diffusion models R Strudel, R Leblond, L Sifre, SEL Dieleman, N Savinov, WS Grathwohl, ... US Patent App. 18/374,447, 2024 | | 2024 |
Sequence-to sequence neural network systems using look ahead tree search RBF Leblond, JB Alayrac, L Sifre, M Pîslar, JB Lespiau, I Antonoglou, ... US Patent App. 18/274,748, 2024 | | 2024 |
Computer code generation from task descriptions using neural networks Y Li, DH Choi, J Chung, NA Kushman, J Schrittwieser, R Leblond, ... US Patent App. 18/105,211, 2023 | | 2023 |