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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 651–700 of 1773 papers

TitleStatusHype
Dependency-Based Self-Attention for Transformer NMT—0
Dependency-Based Relative Positional Encoding for Transformer NMT—0
Denoising Neural Machine Translation Training with Trusted Data and Online Data Selection—0
An Empirical Study of Mini-Batch Creation Strategies for Neural Machine Translation—0
Addressing word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages—0
Defining Boundaries: The Impact of Domain Specification on Cross-Language and Cross-Domain Transfer in Machine Translation—0
Beyond BLEU:Training Neural Machine Translation with Semantic Similarity—0
DeepSumm -- Deep Code Summaries using Neural Transformer Architecture—0
An Empirical Study of Document-to-document Neural Machine Translation—0
Deep Neural Machine Translation with Linear Associative Unit—0
Decoding with Value Networks for Neural Machine Translation—0
Better OOV Translation with Bilingual Terminology Mining—0
Addressing Troublesome Words in Neural Machine Translation—0
A Comprehensive Survey of Multilingual Neural Machine Translation—0
Decoding-History-Based Adaptive Control of Attention for Neural Machine Translation—0
Decoding and Diversity in Machine Translation—0
Better Datastore, Better Translation: Generating Datastores from Pre-Trained Models for Nearest Neural Machine Translation—0
BERTology for Machine Translation: What BERT Knows about Linguistic Difficulties for Translation—0
An Empirical Investigation of Multi-bridge Multilingual NMT models—0
Debiasing Word Embeddings Improves Multimodal Machine Translation—0
DC-MBR: Distributional Cooling for Minimum Bayesian Risk Decoding—0
Data Weighted Training Strategies for Grammatical Error Correction—0
Data Selection with Feature Decay Algorithms Using an Approximated Target Side—0
BERT-JAM: Boosting BERT-Enhanced Neural Machine Translation with Joint Attention—0
An Empirical Comparison of Simple Domain Adaptation Methods for Neural Machine Translation—0
Data Selection Curriculum for Neural Machine Translation—0
Data Scaling Laws in NMT: The Effect of Noise and Architecture—0
BERT Enhanced Neural Machine Translation and Sequence Tagging Model for Chinese Grammatical Error Diagnosis—0
Bering Lab’s Submissions on WAT 2021 Shared Task—0
Data Augmentation With Back translation for Low Resource languages: A case of English and Luganda—0
Data augmentation using back-translation for context-aware neural machine translation—0
Benefits of Data Augmentation for NMT-based Text Normalization of User-Generated Content—0
Data Augmentation to Address Out-of-Vocabulary Problem in Low-Resource Sinhala-English Neural Machine Translation—0
Data Augmentation for Sign Language Gloss Translation—0
Benchmarking Neural and Statistical Machine Translation on Low-Resource African Languages—0
An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation—0
An Empirical Analysis of NMT-Derived Interlingual Embeddings and their Use in Parallel Sentence Identification—0
A Comprehensive Survey of Grammar Error Correction—0
A Character-Aware Encoder for Neural Machine Translation—0
Self-attention based end-to-end Hindi-English Neural Machine Translation—0
DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation—0
Cyber Risks of Machine Translation Critical Errors : Arabic Mental Health Tweets as a Case Study—0
Curriculum Learning and Minibatch Bucketing in Neural Machine Translation—0
Current Shortcomings of Machine Translation in Spanish and Bulgarian Vis-à-vis English—0
Benchmarking Azerbaijani Neural Machine Translation—0
An Effective Optimization Method for Neural Machine Translation: The Case of English-Persian Bilingually Low-Resource Scenario—0
CUNI Transformer Neural MT System for WMT18—0
Being Generous with Sub-Words towards Small NMT Children—0
CUNI Systems in WMT21: Revisiting Backtranslation Techniques for English-Czech NMT—0
CUNI System for the Building Educational Applications 2019 Shared Task: Grammatical Error Correction—0
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