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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 181–190 of 1773 papers

TitleStatusHype
Fully Character-Level Neural Machine Translation without Explicit SegmentationCode0
An Operation Sequence Model for Explainable Neural Machine TranslationCode0
Fine-grained Human Evaluation of Transformer and Recurrent Approaches to Neural Machine Translation for English-to-ChineseCode0
Fine-Tuning MT systems for Robustness to Second-Language Speaker VariationsCode0
Finding Better Subword Segmentation for Neural Machine TranslationCode0
Achieving Open Vocabulary Neural Machine Translation with Hybrid Word-Character ModelsCode0
Finding Memo: Extractive Memorization in Constrained Sequence Generation TasksCode0
First the worst: Finding better gender translations during beam searchCode0
Gender Inflected or Bias Inflicted: On Using Grammatical Gender Cues for Bias Evaluation in Machine TranslationCode0
Guiding attention in Sequence-to-sequence models for Dialogue Act predictionCode0
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