| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 4918 | 2021 |
| Rethinking attention with performers K Choromanski, V Likhosherstov, D Dohan, X Song, A Gane, T Sarlos, ... arXiv preprint arXiv:2009.14794, 2020 | 1874 | 2020 |
| On the opportunities and risks of foundation models. arXiv R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258 10, 2021 | 198 | 2021 |
| & Liang, P.(2021). On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 0 | 127 | |
| On the opportunities and risks of foundation models. arXiv 2021 R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S Von Arx, ... arXiv preprint arXiv:2108.07258, 2023 | 115 | 2023 |
| Masked language modeling for proteins via linearly scalable long-context transformers K Choromanski, V Likhosherstov, D Dohan, X Song, A Gane, T Sarlos, ... arXiv preprint arXiv:2006.03555, 2020 | 112 | 2020 |
| Decentralized training of foundation models in heterogeneous environments B Yuan, Y He, J Davis, T Zhang, T Dao, B Chen, PS Liang, C Re, C Zhang Advances in Neural Information Processing Systems 35, 25464-25477, 2022 | 96 | 2022 |
| Rethinking attention with performers. arXiv 2020 K Choromanski, V Likhosherstov, D Dohan, X Song, A Gane, T Sarlos, ... arXiv preprint arXiv:2009.14794 10, 0 | 83 | |
| On the opportunities and risks of foundation models (arXiv: 2108.07258). arXiv R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S Von Arx, ... | 81 | 2022 |
| The shift from models to compound ai systems M Zaharia, O Khattab, L Chen, JQ Davis, H Miller, C Potts, J Zou, ... Berkeley Artificial Intelligence Research Lab. Available online at: https …, 2024 | 78 | 2024 |
| Controlling commercial cooling systems using reinforcement learning J Luo, C Paduraru, O Voicu, Y Chervonyi, S Munns, J Li, C Qian, P Dutta, ... arXiv preprint arXiv:2211.07357, 2022 | 37 | 2022 |
| Are more llm calls all you need? towards scaling laws of compound inference systems L Chen, JQ Davis, B Hanin, P Bailis, I Stoica, M Zaharia, J Zou arXiv preprint arXiv:2403.02419, 2024 | 34 | 2024 |
| Ode to an ODE KM Choromanski, JQ Davis, V Likhosherstov, X Song, JJ Slotine, J Varley, ... Advances in neural information processing systems 33, 3338-3350, 2020 | 30 | 2020 |
| Sub-linear memory: How to make performers slim V Likhosherstov, KM Choromanski, JQ Davis, X Song, A Weller Advances in Neural Information Processing Systems 34, 6707-6719, 2021 | 21 | 2021 |
| Catformer: Designing stable transformers via sensitivity analysis JQ Davis, A Gu, K Choromanski, T Dao, C Re, C Finn, P Liang International Conference on Machine Learning, 2489-2499, 2021 | 20 | 2021 |
| Time dependence in non-autonomous neural odes JQ Davis, K Choromanski, J Varley, H Lee, JJ Slotine, V Likhosterov, ... arXiv preprint arXiv:2005.01906, 2020 | 17 | 2020 |
| Semi-analytical industrial cooling system model for reinforcement learning Y Chervonyi, P Dutta, P Trochim, O Voicu, C Paduraru, C Qian, ... arXiv preprint arXiv:2207.13131, 2022 | 13 | 2022 |
| Stochastic flows and geometric optimization on the orthogonal group K Choromanski, D Cheikhi, J Davis, V Likhosherstov, A Nazaret, ... International Conference on Machine Learning, 1918-1928, 2020 | 9 | 2020 |
| Are more LLM calls all you need? towards the scaling properties of compound AI systems L Chen, JQ Davis, B Hanin, P Bailis, I Stoica, MA Zaharia, JY Zou Advances in Neural Information Processing Systems 37, 45767-45790, 2024 | 8 | 2024 |
| UFO-BLO: Unbiased first-order bilevel optimization V Likhosherstov, X Song, K Choromanski, J Davis, A Weller arXiv preprint arXiv:2006.03631, 2020 | 6 | 2020 |