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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 826–850 of 1773 papers

TitleStatusHype
Document Graph for Neural Machine Translation—0
Reciprocal Supervised Learning Improves Neural Machine TranslationCode0
Efforts Towards Developing a Tamang Nepali Machine Translation System—0
Effective Use of Target-side Context for Neural Machine Translation—0
Bridging Philippine Languages With Multilingual Neural Machine Translation—0
Domain Adaptation of NMT models for English-Hindi Machine Translation Task : AdapMT Shared Task ICON 2020—0
A Document-Level Neural Machine Translation Model with Dynamic Caching Guided by Theme-Rheme InformationCode0
An Error-based Investigation of Statistical and Neural Machine Translation Performance on Hindi-to-Tamil and English-to-Tamil—0
Terminology-Aware Sentence Mining for NMT Domain Adaptation: ADAPT’s Submission to the Adap-MT 2020 English-to-Hindi AI Translation Shared Task—0
Meta Ensemble for Japanese-Chinese Neural Machine Translation: Kyoto-U+ECNU Participation to WAT 2020—0
Korean-to-Japanese Neural Machine Translation System using Hanja Information—0
Knowledge Graph Enhanced Neural Machine Translation via Multi-task Learning on Sub-entity Granularity—0
Machine-oriented NMT Adaptation for Zero-shot NLP tasks: Comparing the Usefulness of Close and Distant Languages—0
PhraseOut: A Code Mixed Data Augmentation Method for MultilingualNeural Machine Tranlsation—0
Neural Machine Translation Doesn’t Translate Gender Coreference Right Unless You Make ItCode0
Investigating Low-resource Machine Translation for English-to-Tamil—0
BERT Enhanced Neural Machine Translation and Sequence Tagging Model for Chinese Grammatical Error Diagnosis—0
NICT‘s Submission To WAT 2020: How Effective Are Simple Many-To-Many Neural Machine Translation Models?—0
An Effective Optimization Method for Neural Machine Translation: The Case of English-Persian Bilingually Low-Resource Scenario—0
NLPRL Odia-English: Indic Language Neural Machine Translation System—0
Improving NMT via Filtered Back Translation—0
Neural Machine Translation for translating into Croatian and Serbian—0
Neural Machine Translation Models with Back-Translation for the Extremely Low-Resource Indigenous Language BribriCode0
Improving Low-Resource NMT through Relevance Based Linguistic Features Incorporation—0
Identifying Complaints from Product Reviews: A Case Study on HindiCode0
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