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Recent work in multilingual translation advances translation quality surpassing bilingual baselines using deep transformer models with increased capacity.
Learning deep transformer models for machine translation
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Massively multilingual neural machine translation in the wild: Findings and challenges
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Unsupervised cross-lingual representation learning at scale
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Balancing training for multilingual neural machine translation
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Improving massively multilingual neural machine translation and zero-shot translation
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Deep encoder, shallow decoder: Reevaluating the speed-quality tradeoff in machine translation
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
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Convolutional sequence to sequence learning
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Google’s multilingual neural machine translation system: Enabling zero-shot translation
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Speeding up neural machine translation decoding by shrinking run-time vocabulary
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Attention is all you need
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Multi-task learning for multiple language translation
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Multi-way, multilingual neural machine translation with a shared attention mechanism
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Massively multilingual neural machine translation
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Multilingual translation with extensible multilingual pretraining and finetuning
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