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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 351–400 of 1773 papers

TitleStatusHype
Diving Deep into Context-Aware Neural Machine Translation—0
Controlling Utterance Length in NMT-based Word Segmentation with Attention—0
A User-Study on Online Adaptation of Neural Machine Translation to Human Post-Edits—0
Coreference and Coherence in Neural Machine Translation: A Study Using Oracle Experiments—0
Corpora for Document-Level Neural Machine Translation—0
Corpus Augmentation by Sentence Segmentation for Low-Resource Neural Machine Translation—0
Correcting Length Bias in Neural Machine Translation—0
Cost-Effective Training in Low-Resource Neural Machine Translation—0
Cost-Effective Training in Low-Resource Neural Machine Translation—0
Coverage Embedding Models for Neural Machine Translation—0
Crafting Adversarial Examples for Neural Machine Translation—0
CREAMT: Creativity and narrative engagement of literary texts translated by translators and NMT—0
Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models --- Is Single-Corpus Evaluation Enough?—0
Automatic Bilingual Phrase Dictionary Construction from GIZA++ Output—0
Context-Adaptive Document-Level Neural Machine Translation—0
Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation—0
Cross-Lingual Transformers for Neural Automatic Post-Editing—0
Crowd-sourced Phrase-Based Tokenization for Low-Resourced Neural Machine Translation: The case of Fon Language—0
A Multi-task Multi-stage Transitional Training Framework for Neural Chat Translation—0
CSP:Code-Switching Pre-training for Neural Machine Translation—0
Automatic Translation for Multiple NLP tasks: a Multi-task Approach to Machine-oriented NMT Adaptation—0
CUNI English-Czech and English-Polish Systems in WMT20: Robust Document-Level Training—0
Content Word Aware Neural Machine Translation—0
CUNI NMT System for WAT 2018 Translation Tasks—0
CUNI System for the Building Educational Applications 2019 Shared Task: Grammatical Error Correction—0
CUNI Systems in WMT21: Revisiting Backtranslation Techniques for English-Czech NMT—0
CUNI Transformer Neural MT System for WMT18—0
Content-Equivalent Translated Parallel News Corpus and Extension of Domain Adaptation for NMT—0
Current Shortcomings of Machine Translation in Spanish and Bulgarian Vis-à-vis English—0
Curriculum Learning and Minibatch Bucketing in Neural Machine Translation—0
A Transformer-Based Multi-Source Automatic Post-Editing System—0
DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation—0
Adaptive Bridge between Training and Inference for Dialogue Generation—0
Data Augmentation to Address Out-of-Vocabulary Problem in Low-Resource Sinhala-English Neural Machine Translation—0
Data augmentation using back-translation for context-aware neural machine translation—0
Data Augmentation With Back translation for Low Resource languages: A case of English and Luganda—0
Contact Relatedness can help improve multilingual NMT: Microsoft STCI-MT @ WMT20—0
Construction of an Evaluation Corpus for Grammatical Error Correction for Learners of Japanese as a Second Language—0
Data Scaling Laws in NMT: The Effect of Noise and Architecture—0
Data Selection Curriculum for Neural Machine Translation—0
Data Selection with Feature Decay Algorithms Using an Approximated Target Side—0
Data Weighted Training Strategies for Grammatical Error Correction—0
A Test Suite for Evaluating Discourse Phenomena in Document-level Neural Machine Translation—0
Debiasing Word Embeddings Improves Multimodal 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
Decoding and Diversity in Machine Translation—0
Decoding-History-Based Adaptive Control of Attention for Neural Machine Translation—0
Decoding with Value Networks for Neural Machine Translation—0
Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval—0
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