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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 391–400 of 1773 papers

TitleStatusHype
Data Selection with Feature Decay Algorithms Using an Approximated Target Side—0
Data Weighted Training Strategies for Grammatical Error Correction—0
A Test Suite for Evaluating Discourse Phenomena in Document-level Neural Machine Translation—0
Debiasing Word Embeddings Improves Multimodal Machine Translation—0
BERTology for Machine Translation: What BERT Knows about Linguistic Difficulties for Translation—0
An Empirical Investigation of Multi-bridge Multilingual NMT models—0
Decoding and Diversity in Machine Translation—0
Decoding-History-Based Adaptive Control of Attention for Neural Machine Translation—0
Decoding with Value Networks for Neural Machine Translation—0
Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval—0
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