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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 1251–1300 of 1773 papers

TitleStatusHype
Depth Growing for Neural Machine TranslationCode0
Improving Robustness in Real-World Neural Machine Translation Engines—0
Sentence-Level Agreement for Neural Machine Translation—0
English-Indonesian Neural Machine Translation for Spoken Language Domains—0
Better OOV Translation with Bilingual Terminology Mining—0
Unsupervised Pretraining for Neural Machine Translation Using Elastic Weight Consolidation—0
Using Semantic Similarity as Reward for Reinforcement Learning in Sentence Generation—0
Reducing Word Omission Errors in Neural Machine Translation: A Contrastive Learning Approach—0
Look Harder: A Neural Machine Translation Model with Hard Attention—0
Beyond BLEU:Training Neural Machine Translation with Semantic Similarity—0
Multilingual Unsupervised NMT using Shared Encoder and Language-Specific Decoders—0
Effective Adversarial Regularization for Neural Machine TranslationCode1
A Compact and Language-Sensitive Multilingual Translation Method—0
Self-Supervised Neural Machine TranslationCode0
On the Word Alignment from Neural Machine Translation—0
Neural Fuzzy Repair: Integrating Fuzzy Matches into Neural Machine Translation—0
Saliency-driven Word Alignment Interpretation for Neural Machine TranslationCode0
Evaluating the Supervised and Zero-shot Performance of Multi-lingual Translation Models—0
Neural Machine Translating from Natural Language to SPARQLCode1
Incremental Adaptation of NMT for Professional Post-editors: A User Study—0
Improving Zero-shot Translation with Language-Independent Constraints—0
ENCORE: Ensemble Learning using Convolution Neural Machine Translation for Automatic Program Repair—0
Conflict as an Inverse of Attention in Sequence Relationship—0
Multilingual Multi-Domain Adaptation Approaches for Neural Machine Translation—0
Adaptation of Machine Translation Models with Back-translated Data using Transductive Data Selection Methods—0
A Multi-Task Architecture on Relevance-based Neural Query Translation—0
Generalizing Back-Translation in Neural Machine Translation—0
Tagged Back-Translation—0
Unsupervised Question Answering by Cloze TranslationCode0
Monotonic Infinite Lookback Attention for Simultaneous Machine Translation—0
Shared-Private Bilingual Word Embeddings for Neural Machine Translation—0
Unsupervised Pivot Translation for Distant Languages—0
Robust Neural Machine Translation with Doubly Adversarial Inputs—0
Bridging the Gap between Training and Inference for Neural Machine Translation—0
From Balustrades to Pierre Vinken: Looking for Syntax in Transformer Self-Attentions—0
Exploiting Sentential Context for Neural Machine Translation—0
Lattice-Based Transformer Encoder for Neural Machine Translation—0
Post-editing Productivity with Neural Machine Translation: An Empirical Assessment of Speed and Quality in the Banking and Finance Domain—0
Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations—0
Domain Adaptation of Neural Machine Translation by Lexicon InductionCode1
Domain Adaptive Inference for Neural Machine Translation—0
Incorporating Source-Side Phrase Structures into Neural Machine Translation—0
Neural Machine Translation between Myanmar (Burmese) and Rakhine (Arakanese)—0
Improving Neural Machine Translation with Neural Syntactic Distance—0
Unsupervised Extraction of Partial Translations for Neural Machine Translation—0
Online Distilling from Checkpoints for Neural Machine Translation—0
One Size Does Not Fit All: Comparing NMT Representations of Different Granularities—0
Revisiting NMT for Normalization of Early English LettersCode0
Examining Structure of Word Embeddings with PCA—0
Unbabel's Submission to the WMT2019 APE Shared Task: BERT-based Encoder-Decoder for Automatic Post-Editing—0
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