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 | 4572 | 2023 |
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 | 651 | 2021 |
No language left behind: Scaling human-centered machine translation MR Costa-jussà, J Cross, O Çelebi, M Elbayad, K Heafield, K Heffernan, ... arXiv preprint arXiv:2207.04672, 2022 | 435 | 2022 |
BASE Layers: Simplifying Training of Large, Sparse Models L Lewis, Mike and Bhosale, Shruti and Dettmers, Tim and Goyal, Naman and ... International Conference on Machine Learning, 2021 | 171 | 2021 |
Efficient Large Scale Language Modeling with Mixtures of Experts M Artetxe, S Bhosale, N Goyal, T Mihaylov, M Ott, S Shleifer, XV Lin, J Du, ... EMNLP 2022, 2021 | 122* | 2021 |
Facebook AI’s WMT21 News Translation Task Submission C Tran, S Bhosale, J Cross, P Koehn, S Edunov, A Fan Proceedings of the Sixth Conference on Machine Translation, 205-215, 2021 | 85 | 2021 |
Jingfei Du, et al. 2021. Few-shot learning with multilingual language models XV Lin, T Mihaylov, M Artetxe, T Wang, S Chen, D Simig, M Ott, N Goyal, ... arXiv preprint arXiv:2112.10668, 35-40, 2021 | 73 | 2021 |
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 | 50 | 2023 |
Fairscale: A general purpose modular pytorch library for high performance and large scale training M Baines, S Bhosale, V Caggiano, N Goyal, S Goyal, M Ott, B Lefaudeux, ... | 44 | 2021 |
Few-shot learning with multilingual language models XV Lin, T Mihaylov, M Artetxe, T Wang, S Chen, D Simig, M Ott, N Goyal, ... EMNLP 2022, 2021 | 40 | 2021 |
Few-shot learning with multilingual generative language models XV Lin, T Mihaylov, M Artetxe, T Wang, S Chen, D Simig, M Ott, N Goyal, ... Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 35 | 2022 |
Multilingual Machine Translation with Hyper-Adapters C Baziotis, M Artetxe, J Cross, S Bhosale EMNLP 2022, 2022 | 21 | 2022 |
Tricks for Training Sparse Translation Models D Dua, S Bhosale, V Goswami, J Cross, M Lewis, A Fan Proceedings of the 2021 Conference of the North American Chapter of the …, 2021 | 20 | 2021 |
Detecting promotional content in wikipedia S Bhosale, H Vinicombe, R Mooney Proceedings of the 2013 Conference on Empirical Methods in Natural Language …, 2013 | 19 | 2013 |
Causes and cures for interference in multilingual translation U Shaham, M Elbayad, V Goswami, O Levy, S Bhosale arXiv preprint arXiv:2212.07530, 2022 | 16 | 2022 |
Data Selection Curriculum for Neural Machine Translation T Mohiuddin, P Koehn, V Chaudhary, J Cross, S Bhosale, S Joty Findings of EMNLP 2022, 2022 | 12 | 2022 |
Revisiting machine translation for cross-lingual classification M Artetxe, V Goswami, S Bhosale, A Fan, L Zettlemoyer arXiv preprint arXiv:2305.14240, 2023 | 9 | 2023 |
Language Models not just for Pre-training: Fast Online Neural Noisy Channel Modeling S Bhosale, K Yee, S Edunov, M Auli Proceedings of the 5th Conference on Machine Translation (WMT), 584–593, 2020 | 8 | 2020 |
University of Texas at Austin KBP 2013 Slot Filling System: Bayesian Logic Programs for Textual Inference. Y Bentor, A Harrison, S Bhosale, RJ Mooney TAC, 2013 | 8 | 2013 |
Fixing moe over-fitting on low-resource languages in multilingual machine translation M Elbayad, A Sun, S Bhosale arXiv preprint arXiv:2212.07571, 2022 | 4 | 2022 |