| Megatron-lm: Training multi-billion parameter language models using model parallelism M Shoeybi, M Patwary, R Puri, P LeGresley, J Casper, B Catanzaro arXiv preprint arXiv:1909.08053, 2019 | 1454 | 2019 |
| Bloom: A 176b-parameter open-access multilingual language model T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ... | 1308 | 2023 |
| Deep voice: Real-time neural text-to-speech SÖ Arık, M Chrzanowski, A Coates, G Diamos, A Gibiansky, Y Kang, X Li, ... International conference on machine learning, 195-204, 2017 | 796 | 2017 |
| Using deepspeed and megatron to train megatron-turing nlg 530b, a large-scale generative language model S Smith, M Patwary, B Norick, P LeGresley, S Rajbhandari, J Casper, ... arXiv preprint arXiv:2201.11990, 2022 | 537 | 2022 |
| Efficient large-scale language model training on gpu clusters using megatron-lm D Narayanan, M Shoeybi, J Casper, P LeGresley, M Patwary, ... Proceedings of the International Conference for High Performance Computing …, 2021 | 486 | 2021 |
| On the use of the Ffowcs Williams-Hawkings equation to predict far-field jet noise from large-eddy simulations S Mendez, M Shoeybi, SK Lele, P Moin International Journal of Aeroacoustics 12 (1-2), 1-20, 2013 | 152 | 2013 |
| Training question answering models from synthetic data R Puri, R Spring, M Patwary, M Shoeybi, B Catanzaro arXiv preprint arXiv:2002.09599, 2020 | 145 | 2020 |
| MEGATRON-CNTRL: Controllable story generation with external knowledge using large-scale language models P Xu, M Patwary, M Shoeybi, R Puri, P Fung, A Anandkumar, B Catanzaro arXiv preprint arXiv:2010.00840, 2020 | 138 | 2020 |
| Reducing activation recomputation in large transformer models VA Korthikanti, J Casper, S Lym, L McAfee, M Andersch, M Shoeybi, ... Proceedings of Machine Learning and Systems 5, 341-353, 2023 | 129 | 2023 |
| BioMegatron: larger biomedical domain language model HC Shin, Y Zhang, E Bakhturina, R Puri, M Patwary, M Shoeybi, R Mani Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 122 | 2020 |
| Long-short transformer: Efficient transformers for language and vision C Zhu, W Ping, C Xiao, M Shoeybi, T Goldstein, A Anandkumar, ... Advances in neural information processing systems 34, 17723-17736, 2021 | 115 | 2021 |
| Factuality enhanced language models for open-ended text generation N Lee, W Ping, P Xu, M Patwary, PN Fung, M Shoeybi, B Catanzaro Advances in Neural Information Processing Systems 35, 34586-34599, 2022 | 104 | 2022 |
| Stable and accurate schemes for the compressible Navier–Stokes equations K Mattsson, M Svärd, M Shoeybi Journal of Computational Physics 227 (4), 2293-2316, 2008 | 99 | 2008 |
| Fp8 formats for deep learning P Micikevicius, D Stosic, N Burgess, M Cornea, P Dubey, R Grisenthwaite, ... arXiv preprint arXiv:2209.05433, 2022 | 95 | 2022 |
| Unsupervised video interpolation using cycle consistency FA Reda, D Sun, A Dundar, M Shoeybi, G Liu, KJ Shih, A Tao, J Kautz, ... Proceedings of the IEEE/CVF international conference on computer Vision, 892-900, 2019 | 90 | 2019 |
| End-to-end training of neural retrievers for open-domain question answering DS Sachan, M Patwary, M Shoeybi, N Kant, W Ping, WL Hamilton, ... arXiv preprint arXiv:2101.00408, 2021 | 84 | 2021 |
| Retrieval meets long context large language models P Xu, W Ping, X Wu, L McAfee, C Zhu, Z Liu, S Subramanian, ... arXiv preprint arXiv:2310.03025, 2023 | 59 | 2023 |
| Numerical investigation of the acoustic behavior of a multi-perforated liner J Eldredge, D Bodony, M Shoeybi 13th AIAA/CEAS aeroacoustics conference (28th AIAA aeroacoustics conference …, 2007 | 54 | 2007 |
| An adaptive implicit–explicit scheme for the DNS and LES of compressible flows on unstructured grids M Shoeybi, M Svärd, FE Ham, P Moin Journal of Computational Physics 229 (17), 5944-5965, 2010 | 52 | 2010 |
| Vila: On pre-training for visual language models J Lin, H Yin, W Ping, P Molchanov, M Shoeybi, S Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 49 | 2024 |
