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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 601–625 of 1773 papers

TitleStatusHype
CUNI Systems in WMT21: Revisiting Backtranslation Techniques for English-Czech NMT—0
Contrastive Learning for Context-aware Neural Machine Translation Using Coreference Information—0
Adaptive Bridge between Training and Inference for Dialogue Generation—0
FJWU Participation for the WMT21 Biomedical Translation Task—0
Fix-Filter-Fix: Intuitively Connect Any Models for Effective Bug Fixing—0
Sometimes We Want Ungrammatical TranslationsCode0
The TALP-UPC Participation in WMT21 News Translation Task: an mBART-based NMT Approach—0
Illinois Japanese English News Translation for WMT 2021—0
Neural Machine Translation with Heterogeneous Topic Knowledge EmbeddingsCode0
Two Heads are Better than One? Verification of Ensemble Effect in Neural Machine Translation—0
Wino-X: Multilingual Winograd Schemas for Commonsense Reasoning and Coreference ResolutionCode0
eTranslation’s Submissions to the WMT 2021 News Translation Task—0
Adam Mickiewicz University’s English-Hausa Submissions to the WMT 2021 News Translation Task—0
Multi-Class Grammatical Error Detection for Correction: A Tale of Two SystemsCode0
Encouraging Lexical Translation Consistency for Document-Level Neural Machine Translation—0
How should human translation coexist with NMT? Efficient tool for building high quality parallel corpus—0
Empirical Analysis of Korean Public AI Hub Parallel Corpora and in-depth Analysis using LIWC—0
Adaptive Bridge between Training and Inference for Dialogue—0
Continual Learning in Multilingual NMT via Language-Specific Embeddings—0
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters—0
Can Synthetic Translations Improve Bitext Quality?—0
A Two-Stage Curriculum Training Framework for NMT—0
Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help?—0
An Empirical Investigation of Multi-bridge Multilingual NMT models—0
Doubly-Trained Adversarial Data Augmentation for Neural Machine TranslationCode0
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