| Llama 2: Open foundation and fine-tuned chat models H Touvron, L Martin, K Stone, P Albert, A Almahairi, Y Babaei, ... arXiv preprint arXiv:2307.09288, 2023 | 13215 | 2023 |
| Dense Passage Retrieval for Open-Domain Question Answering. V Karpukhin, B Oguz, S Min, PSH Lewis, L Wu, S Edunov, D Chen, W Yih EMNLP (1), 6769-6781, 2020 | 3741 | 2020 |
| fairseq: A fast, extensible toolkit for sequence modeling M Ott, S Edunov, A Baevski, A Fan, S Gross, N Ng, D Grangier, M Auli arXiv preprint arXiv:1904.01038, 2019 | 3360 | 2019 |
| The llama 3 herd of models A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, A Letman, A Mathur, ... arXiv preprint arXiv:2407.21783, 2024 | 3019 | 2024 |
| Multilingual denoising pre-training for neural machine translation Y Liu, J Gu, N Goyal, X Li, S Edunov, M Ghazvininejad, M Lewis, ... Transactions of the Association for Computational Linguistics 8, 726-742, 2020 | 1975 | 2020 |
| Understanding back-translation at scale S Edunov, M Ott, M Auli, D Grangier arXiv preprint arXiv:1808.09381, 2018 | 1413 | 2018 |
| Beyond english-centric multilingual machine translation A Fan, S Bhosale, H Schwenk, Z Ma, A El-Kishky, S Goyal, M Baines, ... Journal of Machine Learning Research 22 (107), 1-48, 2021 | 878 | 2021 |
| No Language Left Behind: Scaling Human-Centered Machine Translation N Team, MR Costa-jussà, J Cross, O Çelebi, M Elbayad, K Heafield, ... arXiv e-prints, arXiv: 2207.04672, 2022 | 859* | 2022 |
| Scaling Neural Machine Translation. arXiv e-prints, page M Ott, S Edunov, D Grangier, M Auli arXiv preprint arXiv:1806.00187, 2018 | 687 | 2018 |
| One trillion edges: Graph processing at facebook-scale A Ching, S Edunov, M Kabiljo, D Logothetis, S Muthukrishnan Proceedings of the VLDB Endowment 8 (12), 1804-1815, 2015 | 589 | 2015 |
| Facebook FAIR's WMT19 news translation task submission N Ng, K Yee, A Baevski, M Ott, M Auli, S Edunov arXiv preprint arXiv:1907.06616, 2019 | 444 | 2019 |
| Cloze-driven pretraining of self-attention networks A Baevski, S Edunov, Y Liu, L Zettlemoyer, M Auli arXiv preprint arXiv:1903.07785, 2019 | 282 | 2019 |
| CCMatrix: Mining billions of high-quality parallel sentences on the web H Schwenk, G Wenzek, S Edunov, E Grave, A Joulin arXiv preprint arXiv:1911.04944, 2019 | 247 | 2019 |
| Classical structured prediction losses for sequence to sequence learning S Edunov, M Ott, M Auli, D Grangier, MA Ranzato arXiv preprint arXiv:1711.04956, 2017 | 214 | 2017 |
| Effective long-context scaling of foundation models W Xiong, J Liu, I Molybog, H Zhang, P Bhargava, R Hou, L Martin, ... arXiv preprint arXiv:2309.16039, 2023 | 192 | 2023 |
| Pre-trained language model representations for language generation S Edunov, A Baevski, M Auli arXiv preprint arXiv:1903.09722, 2019 | 176 | 2019 |
| Three and a half degrees of separation S Edunov, C Diuk, IO Filiz, S Bhagat, M Burke Research at Facebook 694, 2016 | 168* | 2016 |
| Playing the lottery with rewards and multiple languages: lottery tickets in rl and nlp H Yu, S Edunov, Y Tian, AS Morcos arXiv preprint arXiv:1906.02768, 2019 | 153 | 2019 |
| The llama 3 herd of models A Grattafiori, A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, ... arXiv e-prints, arXiv: 2407.21783, 2024 | 108 | 2024 |
| On the evaluation of machine translation systems trained with back-translation S Edunov, M Ott, MA Ranzato, M Auli arXiv preprint arXiv:1908.05204, 2019 | 103 | 2019 |
Myle OttGoogle DeepMindPatvirtintas el. paštas google.com