| Language models are few-shot learners T Brown, B Mann, N Ryder, M Subbiah, JD Kaplan, P Dhariwal, ... Advances in neural information processing systems 33, 1877-1901, 2020 | 24331 | 2020 |
| Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ... Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford …, 2020 | 6479 | 2020 |
| Evaluating large language models trained on code M Chen, J Tworek, H Jun, Q Yuan, HPO Pinto, J Kaplan, H Edwards, ... arXiv preprint arXiv:2107.03374, 2021 | 1963 | 2021 |
| Gpt-4 technical report J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ... arXiv preprint arXiv:2303.08774, 2023 | 755 | 2023 |
| Scaling laws for autoregressive generative modeling T Henighan, J Kaplan, M Katz, M Chen, C Hesse, J Jackson, H Jun, ... arXiv preprint arXiv:2010.14701, 2020 | 231 | 2020 |
| Language Models are Few-Shot Learners. 2020. doi: 10.48550 TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ... arxiv, 5-7, 2005 | 146 | 2005 |
| Language models are few-shot learners. arXiv TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ... Computer Science, Computation and Language, 2005 | 138 | 2005 |
| Language models are few-shot learners. CoRR abs/2005.14165 (2020) TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ... URL: https://arxiv. org/abs/2005.14165, 2005 | 70 | 2005 |
| Tensor programs v: Tuning large neural networks via zero-shot hyperparameter transfer G Yang, EJ Hu, I Babuschkin, S Sidor, X Liu, D Farhi, N Ryder, J Pachocki, ... arXiv preprint arXiv:2203.03466, 2022 | 69 | 2022 |
| Tuning large neural networks via zero-shot hyperparameter transfer G Yang, E Hu, I Babuschkin, S Sidor, X Liu, D Farhi, N Ryder, J Pachocki, ... Advances in Neural Information Processing Systems 34, 17084-17097, 2021 | 60 | 2021 |
| Language models are few-shot learners B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, A Neelakantan, ... arXiv preprint arXiv:2005.14165, 2020 | 49 | 2020 |
| The geometry of rank decompositions of matrix multiplication II: 3× 3 matrices G Ballard, C Ikenmeyer, JM Landsberg, N Ryder Journal of Pure and Applied Algebra 223 (8), 3205-3224, 2019 | 24 | 2019 |
| Language models are few-shot learners.[Cs] TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ... Proceedings of 2020 Neural Information Processing Systems, 2020 | 13 | 2020 |
| On the further structure of the finite free convolutions J Leake, N Ryder arXiv preprint arXiv:1811.06382, 2018 | 10 | 2018 |
| Exponential lower bounds on spectrahedral representations of hyperbolicity cones P Raghavendra, N Ryder, N Srivastava, B Weitz Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019 | 9 | 2019 |
| Real stability testing P Raghavendra, N Ryder, N Srivastava arXiv preprint arXiv:1610.00209, 2016 | 9 | 2016 |
| Generalizations of the matching polynomial to the multivariate independence polynomial J Leake, N Ryder arXiv preprint arXiv:1610.00805, 2016 | 8 | 2016 |
| Generalizations of the matching polynomial to the multivariate independence polynomial JD Leake, NR Ryder Algebraic Combinatorics 2 (5), 781-802, 2019 | 6 | 2019 |
| Connecting the q-multiplicative convolution and the finite difference convolution J Leake, N Ryder Advances in Mathematics 374, 107334, 2020 | 4 | 2020 |
| 8th Innovations in Theoretical Computer Science Conference (ITCS 2017) JR Lee, I Panageas, G Piliouras, Z Allen-Zhu, L Orecchia, T Kaufman, ... Schloss Dagstuhl-Leibniz-Zentrum für Informatik GmbH, 2017 | 2 | 2017 |
