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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 1701–1725 of 1773 papers

TitleStatusHype
Filtering Back-Translated Data in Unsupervised Neural Machine Translation—0
Finding Sami Cognates with a Character-Based NMT Approach—0
Findings of the Fourth Workshop on Neural Generation and Translation—0
Findings of the WMT 2018 Shared Task on Automatic Post-Editing—0
Findings of the WMT 2020 Shared Task on Automatic Post-Editing—0
Finding the Right Recipe for Low Resource Domain Adaptation in Neural Machine Translation—0
Fine-Grained Attention Mechanism for Neural Machine Translation—0
Fine-Grained Error Analysis on English-to-Japanese Machine Translation in the Medical Domain—0
Fine Grained Human Evaluation for English-to-Chinese Machine Translation: A Case Study on Scientific Text—0
Finetuning a Kalaallisut-English machine translation system using web-crawled data—0
First Experiments with Neural Translation of Informal to Formal Mathematics—0
Fix-Filter-Fix: Intuitively Connect Any Models for Effective Bug Fixing—0
Fixing exposure bias with imitation learning needs powerful oracles—0
FJWU Participation for the WMT21 Biomedical Translation Task—0
Flow-Adapter Architecture for Unsupervised Machine Translation—0
Forest-Based Neural Machine Translation—0
FrameNet Annotations Alignment using Attention-based Machine Translation—0
FreeTransfer-X: Safe and Label-Free Cross-Lingual Transfer from Off-the-Shelf Models—0
Frequency-Aware Contrastive Learning for Neural Machine Translation—0
From Balustrades to Pierre Vinken: Looking for Syntax in Transformer Self-Attentions—0
From LLM to NMT: Advancing Low-Resource Machine Translation with Claude—0
Fusing Recency into Neural Machine Translation with an Inter-Sentence Gate Model—0
Future-Prediction-Based Model for Neural Machine Translation—0
GATE X-E : A Challenge Set for Gender-Fair Translations from Weakly-Gendered Languages—0
Gender Aware Spoken Language Translation Applied to English-Arabic—0
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