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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 511–520 of 1773 papers

TitleStatusHype
An Empirical Investigation of Multi-bridge Multilingual NMT models—0
Doubly-Trained Adversarial Data Augmentation for Neural Machine TranslationCode0
On the Complementarity between Pre-Training and Back-Translation for Neural Machine TranslationCode1
Sicilian Translator: A Recipe for Low-Resource NMTCode0
Improving Zero-shot Multilingual Neural Machine Translation for Low-Resource Languages—0
Prose2Poem: The Blessing of Transformers in Translating Prose to Persian PoetryCode0
On the Effectiveness of Quasi Character-Level Models for Machine Translation—0
TransSlowDown: Efficiency Attacks on Neural Machine Translation Systems—0
EdinSaar@WMT21: North-Germanic Low-Resource Multilingual NMT—0
Towards Reinforcement Learning for Pivot-based Neural Machine Translation with Non-autoregressive Transformer—0
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