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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 1201–1250 of 1773 papers

TitleStatusHype
Understanding Neural Machine Translation by Simplification: The Case of Encoder-free Models—0
Understanding Pre-Editing for Black-Box Neural Machine Translation—0
Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English—0
Unfolding and Shrinking Neural Machine Translation Ensembles—0
Unified Model Learning for Various Neural Machine Translation—0
Unified NMT models for the Indian subcontinent transcending script-barriers—0
Unified NMT models for the Indian subcontinent, transcending script-barriers—0
Universal Conditional Masked Language Pre-training for Neural Machine Translation—0
Universal Vector Neural Machine Translation With Effective Attention—0
University of Rochester WMT 2017 NMT System Submission—0
Unlocking Parameter-Efficient Fine-Tuning for Low-Resource Language Translation—0
Unraveling Key Factors of Knowledge Distillation—0
Unsupervised Extraction of Partial Translations for Neural Machine Translation—0
Unsupervised Neural Machine Translation Initialized by Unsupervised Statistical Machine Translation—0
Unsupervised Neural Machine Translation with Future Rewarding—0
Cross-lingual Supervision Improves Unsupervised Neural Machine Translation—0
Unsupervised Pivot Translation for Distant Languages—0
Unsupervised Pretraining for Neural Machine Translation Using Elastic Weight Consolidation—0
Unsupervised Pretraining for Neural Machine Translation Using Elastic Weight Consolidation—0
Unsupervised Source Hierarchies for Low-Resource Neural Machine Translation—0
Unsupervised Transfer Learning in Multilingual Neural Machine Translation with Cross-Lingual Word Embeddings—0
Unveiling the Power of Source: Source-based Minimum Bayes Risk Decoding for Neural Machine Translation—0
Usefulness of Emotional Prosody in Neural Machine Translation—0
Using Context in Neural Machine Translation Training Objectives—0
Using Images to Improve Machine-Translating E-Commerce Product Listings.—0
Investigating Massive Multilingual Pre-Trained Machine Translation Models for Clinical Domain via Transfer Learning—0
Enhanced back-translation for low resource neural machine translation using self-training—0
Using Semantic Role Labeling to Improve Neural Machine Translation—0
Using Semantic Similarity as Reward for Reinforcement Learning in Sentence Generation—0
Using Spoken Word Posterior Features in Neural Machine Translation—0
Using Target-side Monolingual Data for Neural Machine Translation through Multi-task Learning—0
Utilizing Monolingual Data in NMT for Similar Languages: Submission to Similar Language Translation Task—0
Validation of Tsallis Entropy In Inter-Modality Neuroimage Registration—0
Variational Neural Machine Translation with Normalizing Flows—0
Variational Recurrent Neural Machine Translation—0
Vector-Vector-Matrix Architecture: A Novel Hardware-Aware Framework for Low-Latency Inference in NLP Applications—0
Visualizing and Understanding Neural Machine Translation—0
Vocabulary Adaptation for Distant Domain Adaptation in Neural Machine Translation—0
What Level of Quality can Neural Machine Translation Attain on Literary Text?—0
What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation—0
What Role Does BERT Play in the Neural Machine Translation Encoder?—0
What Works and Doesn't Work, A Deep Decoder for Neural Machine Translation—0
What Works and Doesn’t Work, A Deep Decoder for Neural Machine Translation—0
When and Why is Unsupervised Neural Machine Translation Useless?—0
When a `sport' is a person and other issues for NMT of novels—0
When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?—0
When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?—0
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation—0
Who Evaluates the Evaluators? On Automatic Metrics for Assessing AI-based Offensive Code Generators—0
Why Find the Right One?—0
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