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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 351–375 of 1773 papers

TitleStatusHype
A Multi-task Multi-stage Transitional Training Framework for Neural Chat Translation—0
Controlling Utterance Length in NMT-based Word Segmentation with Attention—0
A User-Study on Online Adaptation of Neural Machine Translation to Human Post-Edits—0
Coreference and Coherence in Neural Machine Translation: A Study Using Oracle Experiments—0
Corpora for Document-Level Neural Machine Translation—0
Corpus Augmentation by Sentence Segmentation for Low-Resource Neural Machine Translation—0
Correcting Length Bias in Neural Machine Translation—0
Cost-Effective Training in Low-Resource Neural Machine Translation—0
Cost-Effective Training in Low-Resource Neural Machine Translation—0
Coverage Embedding Models for Neural Machine Translation—0
Crafting Adversarial Examples for Neural Machine Translation—0
CREAMT: Creativity and narrative engagement of literary texts translated by translators and NMT—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
Content Word Aware Neural Machine Translation—0
Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation—0
Cross-Lingual Transformers for Neural Automatic Post-Editing—0
Crowd-sourced Phrase-Based Tokenization for Low-Resourced Neural Machine Translation: The case of Fon Language—0
Content-Equivalent Translated Parallel News Corpus and Extension of Domain Adaptation for NMT—0
CSP:Code-Switching Pre-training for Neural Machine Translation—0
A Transformer-Based Multi-Source Automatic Post-Editing System—0
CUNI English-Czech and English-Polish Systems in WMT20: Robust Document-Level Training—0
Adaptive Bridge between Training and Inference for Dialogue Generation—0
CUNI NMT System for WAT 2018 Translation Tasks—0
Contact Relatedness can help improve multilingual NMT: Microsoft STCI-MT @ WMT20—0
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