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NMT

Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

Papers

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Showing 976–1000 of 1773 papers

TitleStatusHype
Transformer based Multilingual document Embedding model—0
Revisiting Low Resource Status of Indian Languages in Machine Translation—0
The Sockeye 2 Neural Machine Translation Toolkit at AMTA 2020—0
Data Weighted Training Strategies for Grammatical Error Correction—0
Neural Machine Translation with Error CorrectionCode0
Neural Machine Translation model for University Email Application—0
Dual Past and Future for Neural Machine Translation—0
Rewiring the Transformer with Depth-Wise LSTMs—0
Tagged Back-translation Revisited: Why Does It Really Work?—0
Octanove Labs' Japanese-Chinese Open Domain Translation System—0
Modeling Word Formation in English--German Neural Machine Translation—0
Document Translation vs. Query Translation for Cross-Lingual Information Retrieval in the Medical Domain—0
Content Word Aware Neural Machine Translation—0
A Retrieve-and-Rewrite Initialization Method for Unsupervised Machine TranslationCode0
Multi-Task Neural Model for Agglutinative Language Translation—0
Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation—0
Compressing Neural Machine Translation Models with 4-bit Precision—0
SimulSpeech: End-to-End Simultaneous Speech to Text Translation—0
Improving Autoregressive NMT with Non-Autoregressive Model—0
Improving Document-Level Neural Machine Translation with Domain Adaptation—0
Checkpoint Reranking: An Approach to Select Better Hypothesis for Neural Machine Translation Systems—0
Translationese as a Language in ``Multilingual'' NMT—0
NAIST's Machine Translation Systems for IWSLT 2020 Conversational Speech Translation Task—0
Efficient Neural Machine Translation for Low-Resource Languages via Exploiting Related Languages—0
SIGMORPHON 2020 Task 0 System Description: ETH Z\"urich Team—0
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