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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 751–800 of 1773 papers

TitleStatusHype
Rewriter-Evaluator Architecture for Neural Machine Translation—0
Exploring Pair-Wise NMT for Indian Languages—0
Document Graph for Neural Machine Translation—0
Reciprocal Supervised Learning Improves Neural Machine TranslationCode0
The University of Tokyo’s Submissions to the WAT 2020 Shared Task—0
Meta Ensemble for Japanese-Chinese Neural Machine Translation: Kyoto-U+ECNU Participation to WAT 2020—0
Machine-oriented NMT Adaptation for Zero-shot NLP tasks: Comparing the Usefulness of Close and Distant Languages—0
An Error-based Investigation of Statistical and Neural Machine Translation Performance on Hindi-to-Tamil and English-to-Tamil—0
Multimodal Neural Machine Translation for English to Hindi—0
WT: Wipro AI Submissions to the WAT 2020—0
BERT Enhanced Neural Machine Translation and Sequence Tagging Model for Chinese Grammatical Error Diagnosis—0
An Effective Optimization Method for Neural Machine Translation: The Case of English-Persian Bilingually Low-Resource Scenario—0
Improving NMT via Filtered Back Translation—0
NICT‘s Submission To WAT 2020: How Effective Are Simple Many-To-Many Neural Machine Translation Models?—0
A Test Suite for Evaluating Discourse Phenomena in Document-level Neural Machine Translation—0
NLPRL Odia-English: Indic Language Neural Machine Translation System—0
Comparison of the effects of attention mechanism on translation tasks of different lengths of ambiguous words—0
Neural Machine Translation for translating into Croatian and Serbian—0
A Review of Discourse-level Machine Translation—0
Korean-to-Japanese Neural Machine Translation System using Hanja Information—0
Efforts Towards Developing a Tamang Nepali Machine Translation System—0
Domain Adaptation of NMT models for English-Hindi Machine Translation Task : AdapMT Shared Task ICON 2020—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
Identifying Complaints from Product Reviews: A Case Study on HindiCode0
PhraseOut: A Code Mixed Data Augmentation Method for MultilingualNeural Machine Tranlsation—0
Punjabi to English Bidirectional NMT System—0
MUCS@Adap-MT 2020: Low Resource Domain Adaptation for Indic Machine Translation—0
AdapNMT : Neural Machine Translation with Technical Domain Adaptation for Indic Languages—0
Neural Machine Translation Doesn’t Translate Gender Coreference Right Unless You Make ItCode0
Bridging Philippine Languages With Multilingual Neural Machine Translation—0
Zero-shot translation among Indian languages—0
Zero-Shot Neural Machine Translation: Russian-Hindi @LoResMT 2020—0
Investigating Low-resource Machine Translation for English-to-Tamil—0
Effective Use of Target-side Context for Neural Machine Translation—0
A Document-Level Neural Machine Translation Model with Dynamic Caching Guided by Theme-Rheme InformationCode0
Knowledge Graph Enhanced Neural Machine Translation via Multi-task Learning on Sub-entity Granularity—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
ContraCAT: Contrastive Coreference Analytical Templates for Machine Translation—0
Filtering Back-Translated Data in Unsupervised Neural Machine Translation—0
Meet Changes with Constancy: Learning Invariance in Multi-Source Translation—0
Multilingual Neural Machine Translation—0
Heterogeneous Recycle Generation for Chinese Grammatical Error Correction—0
Training with Adversaries to Improve Faithfulness of Attention in Neural Machine Translation—0
English-to-Chinese Transliteration with Phonetic Auxiliary Task—0
SSN-NLP at SemEval-2020 Task 4: Text Classification and Generation on Common Sense Context Using Neural Networks—0
Machine Translation of Novels in the Age of TransformerCode0
Dynamic Curriculum Learning for Low-Resource Neural Machine Translation—0
Decoding and Diversity in Machine Translation—0
Master Thesis: Neural Sign Language Translation by Learning Tokenization—0
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