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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 401–410 of 1773 papers

TitleStatusHype
Competency-Aware Neural Machine Translation: Can Machine Translation Know its Own Translation Quality?Code0
Rank-One Editing of Encoder-Decoder Models—0
A Copy Mechanism for Handling Knowledge Base Elements in SPARQL Neural Machine TranslationCode0
Reducing Hallucinations in Neural Machine Translation with Feature Attribution—0
Easy Guided Decoding in Providing Suggestions for Interactive Machine TranslationCode0
HilMeMe: A Human-in-the-Loop Machine Translation Evaluation Metric Looking into Multi-Word Expressions—0
Parallel Attention Forcing for Machine Translation—0
Finding Memo: Extractive Memorization in Constrained Sequence Generation TasksCode0
Specializing Multi-domain NMT via Penalizing Low Mutual Information—0
Analyzing the Use of Influence Functions for Instance-Specific Data Filtering in Neural Machine Translation—0
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