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02/02/2023
The unreasonable effectiveness of few-shot learning for machine translation
We demonstrate the potential of few-shot translation systems, trained wi...
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05/09/2022
Building Machine Translation Systems for the Next Thousand Languages
In this paper we share findings from our effort to build practical machi...
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02/04/2022
Data Scaling Laws in NMT: The Effect of Noise and Architecture
In this work, we study the effect of varying the architecture and traini...
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12/13/2021
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
Scaling language models with more data, compute and parameters has drive...
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09/16/2021
Scaling Laws for Neural Machine Translation
We present an empirical study of scaling properties of encoder-decoder T...
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05/10/2021
GSPMD: General and Scalable Parallelization for ML Computation Graphs
We present GSPMD, an automatic, compiler-based parallelization system fo...
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06/30/2020
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding
Neural network scaling has been critical for improving the model quality...
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07/11/2019
Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges
We introduce our efforts towards building a universal neural machine tra...
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02/28/2019
Reinforcement Learning based Curriculum Optimization for Neural Machine Translation
We consider the problem of making efficient use of heterogeneous trainin...
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02/21/2019
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Lingvo is a Tensorflow framework offering a complete solution for collab...
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11/14/2016
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation
We propose a simple solution to use a single Neural Machine Translation ...
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09/26/2016