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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 551–575 of 1773 papers

TitleStatusHype
Approches quantitatives de l'analyse des prédictions en traduction automatique neuronale (TAN)—0
A Dynamic Head Importance Computation Mechanism for Neural Machine Translation—0
Adabot: Fault-Tolerant Java Decompiler—0
Dynamic Sentence Sampling for Efficient Training of Neural Machine Translation—0
Dynamic Position Encoding for Transformers—0
Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque—0
A Parallel Corpus of Theses and Dissertations Abstracts—0
Dynamic Oracle for Neural Machine Translation in Decoding Phase—0
Building a Parallel Corpus and Training Translation Models Between Luganda and English—0
Dynamic Fusion: Attentional Language Model for Neural Machine Translation—0
Building a Neural Machine Translation System Using Only Synthetic Parallel Data—0
ANVITA Machine Translation System for WAT 2021 MultiIndicMT Shared Task—0
Adversarial Neural Machine Translation—0
Dynamic Curriculum Learning for Low-Resource Neural Machine Translation—0
Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars—0
Controllable Dual Skew Divergence Loss for Neural Machine Translation—0
Bridging the Gap between Training and Inference for Neural Machine Translation—0
Dual Past and Future for Neural Machine Translation—0
Bridging Philippine Languages With Multilingual Neural Machine Translation—0
Adversarial Grammatical Error Correction—0
Active Learning Approaches to Enhancing Neural Machine Translation—0
D-PAGE: Diverse Paraphrase Generation—0
Bridging Neural Machine Translation and Bilingual Dictionaries—0
Bridging Dialects: Translating Standard Bangla to Regional Variants Using Neural Models—0
Do Multilingual Neural Machine Translation Models Contain Language Pair Specific Attention Heads?—0
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