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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 801–825 of 1773 papers

TitleStatusHype
Investigating Backtranslation in Neural Machine Translation—0
Investigating Catastrophic Forgetting During Continual Training for Neural Machine Translation—0
Investigating Code-Mixed Modern Standard Arabic-Egyptian to English Machine Translation—0
Investigating Failures of Automatic Translation in the Case of Unambiguous Gender—0
Investigating Low-resource Machine Translation for English-to-Tamil—0
Investigating Multilingual NMT Representations at Scale—0
Evaluation of NMT-Assisted Grammar Transfer for a Multi-Language Configurable Data-to-Text System—0
Investigating Terminology Translation in Statistical and Neural Machine Translation: A Case Study on English-to-Hindi and Hindi-to-English—0
Investigation of English to Hindi Multimodal Neural Machine Translation using Transliteration-based Phrase Pairs Augmentation—0
Is 42 the Answer to Everything in Subtitling-oriented Speech Translation?—0
Is context all you need? Scaling Neural Sign Language Translation to Large Domains of Discourse—0
Is it Great or Terrible? Preserving Sentiment in Neural Machine Translation of Arabic Reviews—0
Is LLM the Silver Bullet to Low-Resource Languages Machine Translation?—0
Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation—0
Evaluating the usefulness of neural machine translation for the Polish translators in the European Commission—0
Iterative Batch Back-Translation for Neural Machine Translation: A Conceptual Model—0
Denoising Neural Machine Translation Training with Trusted Data and Online Data Selection—0
Iterative Domain-Repaired Back-Translation—0
Iterative Dual Domain Adaptation for Neural Machine Translation—0
A Hybrid Approach for Improved Low Resource Neural Machine Translation using Monolingual Data—0
Evaluating the Supervised and Zero-shot Performance of Multi-lingual Translation Models—0
Jam or Cream First? Modeling Ambiguity in Neural Machine Translation with SCONES—0
Japanese Predicate Conjugation for Neural Machine Translation—0
Japanese-Russian TMU Neural Machine Translation System using Multilingual Model for WAT 2019—0
Evaluating the Performance of Back-translation for Low Resource English-Marathi Language Pair: CFILT-IITBombay @ LoResMT 2021—0
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