Palm: Scaling language modeling with pathways A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... Journal of Machine Learning Research 24 (240), 1-113, 2023 | 3412 | 2023 |
Model-based reinforcement learning for atari L Kaiser, M Babaeizadeh, P Milos, B Osinski, RH Campbell, ... arXiv preprint arXiv:1903.00374, 2019 | 875 | 2019 |
Program synthesis with large language models J Austin, A Odena, M Nye, M Bosma, H Michalewski, D Dohan, E Jiang, ... arXiv preprint arXiv:2108.07732, 2021 | 654 | 2021 |
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 | 467 | 2023 |
Show your work: Scratchpads for intermediate computation with language models M Nye, AJ Andreassen, G Gur-Ari, H Michalewski, J Austin, D Bieber, ... arXiv preprint arXiv:2112.00114, 2021 | 400 | 2021 |
Solving quantitative reasoning problems with language models A Lewkowycz, A Andreassen, D Dohan, E Dyer, H Michalewski, ... Advances in Neural Information Processing Systems 35, 3843-3857, 2022 | 398 | 2022 |
Rt-2: Vision-language-action models transfer web knowledge to robotic control A Brohan, N Brown, J Carbajal, Y Chebotar, X Chen, K Choromanski, ... arXiv preprint arXiv:2307.15818, 2023 | 276 | 2023 |
Reinforcement learning of theorem proving C Kaliszyk, J Urban, H Michalewski, M Olšák Advances in Neural Information Processing Systems 31, 2018 | 173 | 2018 |
Multi-game decision transformers KH Lee, O Nachum, MS Yang, L Lee, D Freeman, S Guadarrama, ... Advances in Neural Information Processing Systems 35, 27921-27936, 2022 | 156 | 2022 |
Simulation-based reinforcement learning for real-world autonomous driving B Osiński, A Jakubowski, P Zięcina, P Miłoś, C Galias, S Homoceanu, ... 2020 IEEE international conference on robotics and automation (ICRA), 6411-6418, 2020 | 133 | 2020 |
Learning to run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments Ł Kidziński, SP Mohanty, CF Ong, Z Huang, S Zhou, A Pechenko, ... The NIPS'17 Competition: Building Intelligent Systems, 121-153, 2018 | 92 | 2018 |
Palm: Scaling language modeling with pathways. arXiv 2022 A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... arXiv preprint arXiv:2204.02311 10, 2022 | 79 | 2022 |
Sparse is enough in scaling transformers S Jaszczur, A Chowdhery, A Mohiuddin, L Kaiser, W Gajewski, ... Advances in Neural Information Processing Systems 34, 9895-9907, 2021 | 69 | 2021 |
Language model cascades D Dohan, W Xu, A Lewkowycz, J Austin, D Bieber, RG Lopes, Y Wu, ... arXiv preprint arXiv:2207.10342, 2022 | 63 | 2022 |
Rt-2: Vision-language-action models transfer web knowledge to robotic control B Zitkovich, T Yu, S Xu, P Xu, T Xiao, F Xia, J Wu, P Wohlhart, S Welker, ... Conference on Robot Learning, 2165-2183, 2023 | 46 | 2023 |
Small Valdivia compact spaces W Kubiś, H Michalewski Topology and its Applications 153 (14), 2560-2573, 2006 | 46 | 2006 |
Focused transformer: Contrastive training for context scaling S Tworkowski, K Staniszewski, M Pacek, Y Wu, H Michalewski, P Miłoś Advances in Neural Information Processing Systems 36, 2024 | 45 | 2024 |
Promptbreeder: Self-referential self-improvement via prompt evolution C Fernando, D Banarse, H Michalewski, S Osindero, T Rocktäschel arXiv preprint arXiv:2309.16797, 2023 | 42 | 2023 |
Distributed deep reinforcement learning: Learn how to play atari games in 21 minutes I Adamski, R Adamski, T Grel, A Jędrych, K Kaczmarek, H Michalewski High Performance Computing: 33rd International Conference, ISC High …, 2018 | 40 | 2018 |
Hierarchical transformers are more efficient language models P Nawrot, S Tworkowski, M Tyrolski, Ł Kaiser, Y Wu, C Szegedy, ... arXiv preprint arXiv:2110.13711, 2021 | 32 | 2021 |