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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 311–320 of 1773 papers

TitleStatusHype
Finding Memo: Extractive Memorization in Constrained Sequence Generation TasksCode0
Fine-grained Human Evaluation of Transformer and Recurrent Approaches to Neural Machine Translation for English-to-ChineseCode0
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
Ensembling Factored Neural Machine Translation Models for Automatic Post-Editing and Quality EstimationCode0
Consistency by Agreement in Zero-shot Neural Machine TranslationCode0
Enhancing Low-Resource NMT with a Multilingual Encoder and Knowledge Distillation: A Case StudyCode0
Enhancing Assamese NLP Capabilities: Introducing a Centralized Dataset RepositoryCode0
Enhancing Neural Machine Translation with Semantic UnitsCode0
Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based ModelsCode0
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