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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 701–725 of 1773 papers

TitleStatusHype
Beam Search Strategies for Neural Machine Translation—0
Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation—0
CUNI NMT System for WAT 2018 Translation Tasks—0
CUNI NMT System for WAT 2017 Translation Tasks—0
CUNI English-Czech and English-Polish Systems in WMT20: Robust Document-Level Training—0
Automatic Translation for Multiple NLP tasks: a Multi-task Approach to Machine-oriented NMT Adaptation—0
CSP:Code-Switching Pre-training for Neural Machine Translation—0
Crowdsourced Phrase-Based Tokenization for Low-Resourced Neural Machine Translation: The Case of Fon Language—0
Crowd-sourced Phrase-Based Tokenization for Low-Resourced Neural Machine Translation: The case of Fon Language—0
Cross-Lingual Transformers for Neural Automatic Post-Editing—0
Ancient-Modern Chinese Translation with a Large Training Dataset—0
Addressing Asymmetry in Multilingual Neural Machine Translation with Fuzzy Task Clustering—0
A Comprehensive Evaluation of Neural SPARQL Query Generation from Natural Language Questions—0
Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation—0
Cross-lingual Human-Preference Alignment for Neural Machine Translation with Direct Quality Optimization—0
Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models --- Is Single-Corpus Evaluation Enough?—0
Automatic Bilingual Phrase Dictionary Construction from GIZA++ Output—0
An Augmented Translation Technique for low Resource language pair: Sanskrit to Hindi translation—0
CREAMT: Creativity and narrative engagement of literary texts translated by translators and NMT—0
Improving Character-level Japanese-Chinese Neural Machine Translation with Radicals as an Additional Input Feature—0
Improving Character-based Decoding Using Target-Side Morphological Information for Neural Machine Translation—0
Crafting Adversarial Examples for Neural Machine Translation—0
Automatically Generating Commit Messages from Diffs using Neural Machine Translation—0
Coverage Embedding Models for Neural Machine Translation—0
Improving Autoregressive NMT with Non-Autoregressive Model—0
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