Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805, 2023 | 3462 | 2023 |
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 | 1505* | 2022 |
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 1332 | 2024 |
Gemma: Open models based on gemini research and technology G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ... arXiv preprint arXiv:2403.08295, 2024 | 1115 | 2024 |
Magnetic control of tokamak plasmas through deep reinforcement learning J Degrave, F Felici, J Buchli, M Neunert, B Tracey, F Carpanese, T Ewalds, ... Nature 602 (7897), 414-419, 2022 | 948 | 2022 |
Solving mixed integer programs using neural networks V Nair, S Bartunov, F Gimeno, I Von Glehn, P Lichocki, I Lobov, ... arXiv preprint arXiv:2012.13349, 2020 | 328 | 2020 |
Experimental research on the TCV tokamak BP Duval, A Abdolmaleki, M Agostini, CJ Ajay, S Alberti, E Alessi, ... Nuclear Fusion 64 (11), 112023, 2024 | 5 | 2024 |