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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 1501–1550 of 1773 papers

TitleStatusHype
Monolingual and Parallel Corpora for Kangri Low Resource LanguageCode0
HFT: High Frequency Tokens for Low-Resource NMTCode0
Synthetic and Natural Noise Both Break Neural Machine TranslationCode0
Exploiting Social Media Content for Self-Supervised Style TransferCode0
Monolingual Embeddings for Low Resourced Neural Machine TranslationCode0
OpenKiwi: An Open Source Framework for Quality EstimationCode0
Competency-Aware Neural Machine Translation: Can Machine Translation Know its Own Translation Quality?Code0
Morphological and Language-Agnostic Word Segmentation for NMTCode0
Morphologically-Guided Segmentation For Translation of Agglutinative Low-Resource LanguagesCode0
OpenNMT: Open-Source Toolkit for Neural Machine TranslationCode0
When and Why are Pre-trained Word Embeddings Useful for Neural Machine Translation?Code0
When and Why is Document-level Context Useful in Neural Machine Translation?Code0
How do lexical semantics affect translation? An empirical studyCode0
MTCue: Learning Zero-Shot Control of Extra-Textual Attributes by Leveraging Unstructured Context in Neural Machine TranslationCode0
Domain Generalisation of NMT: Fusing Adapters with Leave-One-Domain-Out TrainingCode0
How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation PairsCode0
Verdi: Quality Estimation and Error Detection for Bilingual CorporaCode0
Optimal Transport for Unsupervised Hallucination Detection in Neural Machine TranslationCode0
Unsupervised Question Answering by Cloze TranslationCode0
Optimizing the Training Schedule of Multilingual NMT using Reinforcement LearningCode0
TransIns: Document Translation with Markup ReinsertionCode0
TopicVD: A Topic-Based Dataset of Video-Guided Multimodal Machine Translation for DocumentariesCode0
Multi-Class Grammatical Error Detection for Correction: A Tale of Two SystemsCode0
Multi-Domain Adaptation in Neural Machine Translation Through Multidimensional TaggingCode0
Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine TranslationCode0
Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel DataCode0
Multi-Domain Neural Machine Translation with Word-Level Domain Context DiscriminationCode0
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain MixingCode0
Otem&Utem: Over- and Under-Translation Evaluation Metric for NMTCode0
Translate, then Parse! A strong baseline for Cross-Lingual AMR ParsingCode0
Selective Attention for Context-aware Neural Machine TranslationCode0
Multi-level Community-awareness Graph Neural Networks for Neural Machine TranslationCode0
Multilingual Bidirectional Unsupervised Translation Through Multilingual Finetuning and Back-TranslationCode0
Identifying Complaints from Product Reviews: A Case Study on HindiCode0
BPE beyond Word Boundary: How NOT to use Multi Word Expressions in Neural Machine TranslationCode0
An Operation Sequence Model for Explainable Neural Machine TranslationCode0
Adaptive Weighting for Neural Machine TranslationCode0
Multilingual Extractive Reading Comprehension by Runtime Machine TranslationCode0
Targeted Adversarial Attacks against Neural Machine TranslationCode0
Self-Paced Learning for Neural Machine TranslationCode0
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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