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20182026
most citedMultilingual Denoising Pre-training for Neural Machine Translation

607 citations · 1k across the 23 of their papers we have counts for

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Showing 2021 · cs.CLShow all

10 papers · 2 filters

cs.CL2021★ 14 cited

Efficient Large Scale Language Modeling with Mixtures of Experts

Mikel Artetxe, Shruti Bhosale, Naman Goyal +21

Mixture of Experts layers (MoEs) enable efficient scaling of language models through conditional computation. This paper presents a detailed empirical study of how autoregressive M…

cs.CL2021★ 77 cited

Few-shot Learning with Multilingual Language Models

Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe +18

Large-scale generative language models such as GPT-3 are competitive few-shot learners. While these models are known to be able to jointly represent many different languages, their…

cs.CL2021★ 15 cited

Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs

Peter Hase, Mona Diab, Asli Celikyilmaz +5

Do language models have beliefs about the world? Dennett (1995) famously argues that even thermostats have beliefs, on the view that a belief is simply an informational state decou…

cs.CL2021

Distributionally Robust Multilingual Machine Translation

Chunting Zhou, Daniel Levy, Xian Li +2

Multilingual neural machine translation (MNMT) learns to translate multiple language pairs with a single model, potentially improving both the accuracy and the memory-efficiency of…

cs.CL2021

FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task

Yun Tang, Hongyu Gong, Xian Li +4

In this paper, we describe our end-to-end multilingual speech translation system submitted to the IWSLT 2021 evaluation campaign on the Multilingual Speech Translation shared task.…

cs.CL2021★ 2 cited

Improving Speech Translation by Understanding and Learning from the Auxiliary Text Translation Task

Yun Tang, Juan Pino, Xian Li +2

Pretraining and multitask learning are widely used to improve the speech to text translation performance. In this study, we are interested in training a speech to text translation…