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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 1541–1550 of 1773 papers

TitleStatusHype
An Evaluation of Neural Machine Translation Models on Historical Spelling NormalizationCode0
Impact of Visual Context on Noisy Multimodal NMT: An Empirical Study for English to Indian LanguagesCode0
Competence-based Curriculum Learning for Neural Machine TranslationCode0
Assessing the Importance of Frequency versus Compositionality for Subword-based Tokenization in NMTCode0
Towards a Better Understanding of Variations in Zero-Shot Neural Machine Translation PerformanceCode0
Self-Supervised Neural Machine TranslationCode0
Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine TranslationCode0
Improved Neural Machine Translation with a Syntax-Aware Encoder and DecoderCode0
Multilingual Neural Machine Translation for Zero-Resource LanguagesCode0
Patching Leaks in the Charformer for Efficient Character-Level GenerationCode0
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