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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 12 of 12 1 The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation ... Goyal, Naman; Gao, Cynthia; Chaudhary, Vishrav. - : arXiv, 2021 BASE Show details 2 Multilingual Autoregressive Entity Linking ... De Cao, Nicola; Wu, Ledell; Popat, Kashyap. - : arXiv, 2021 BASE Show details 3 Larger-Scale Transformers for Multilingual Masked Language Modeling ... Goyal, Naman; Du, Jingfei; Ott, Myle. - : arXiv, 2021 BASE Show details 4 FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task ... Tang, Yun; Gong, Hongyu; Li, Xian. - : arXiv, 2021 BASE Show details 5 Few-shot Learning with Multilingual Language Models ... Lin, Xi Victoria; Mihaylov, Todor; Artetxe, Mikel. - : arXiv, 2021 BASE Show details 6 Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data ... Ko, Wei-Jen; El-Kishky, Ahmed; Renduchintala, Adithya. - : arXiv, 2021 BASE Show details 7 Multilingual Translation with Extensible Multilingual Pretraining and Finetuning ... Tang, Yuqing; Tran, Chau; Li, Xian; Chen, Peng-Jen; Goyal, Naman; Chaudhary, Vishrav; Gu, Jiatao; Fan, Angela. - : arXiv, 2020 Abstract: Recent work demonstrates the potential of multilingual pretraining of creating one model that can be used for various tasks in different languages. Previous work in multilingual pretraining has demonstrated that machine translation systems can be created by finetuning on bitext. In this work, we show that multilingual translation models can be created through multilingual finetuning. Instead of finetuning on one direction, a pretrained model is finetuned on many directions at the same time. Compared to multilingual models trained from scratch, starting from pretrained models incorporates the benefits of large quantities of unlabeled monolingual data, which is particularly important for low resource languages where bitext is not available. We demonstrate that pretrained models can be extended to incorporate additional languages without loss of performance. We double the number of languages in mBART to support multilingual machine translation models of 50 languages. Finally, we create the ML50 benchmark, ... : 10 pages (main) + 5 pages (appendices). 9 tables and 2 figures ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2008.00401 https://dx.doi.org/10.48550/arxiv.2008.00401 BASE Hide details 8 Facebook AI's WMT20 News Translation Task Submission ... Chen, Peng-Jen; Lee, Ann; Wang, Changhan. - : arXiv, 2020 BASE Show details 9 Multilingual Denoising Pre-training for Neural Machine Translation ... Liu, Yinhan; Gu, Jiatao; Goyal, Naman. - : arXiv, 2020 BASE Show details 10 Beyond English-Centric Multilingual Machine Translation ... Fan, Angela; Bhosale, Shruti; Schwenk, Holger. - : arXiv, 2020 BASE Show details 11 Unsupervised Cross-lingual Representation Learning at Scale ... Conneau, Alexis; Khandelwal, Kartikay; Goyal, Naman. - : arXiv, 2019 BASE Show details 12 The Social Dynamics of Language Change in Online Networks ... Goel, Rahul; Soni, Sandeep; Goyal, Naman. - : arXiv, 2016 BASE Show details

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