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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 901–950 of 1773 papers

TitleStatusHype
Translation vs Post-editing of NMT Output: Insights from the English-Greek language pair—0
Can Automatic Post-Editing Improve NMT?Code1
Rewriter-Evaluator Framework for Neural Machine Translation—0
Target Conditioning for One-to-Many Generation—0
Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based ModelsCode0
Softmax Tempering for Training Neural Machine Translation Models—0
Long-Short Term Masking Transformer: A Simple but Effective Baseline for Document-level Neural Machine Translation—0
Dissecting Lottery Ticket Transformers: Structural and Behavioral Study of Sparse Neural Machine Translation—0
Code-switching pre-training for neural machine translation—0
Graph-to-Sequence Neural Machine Translation—0
Document-level Neural Machine Translation with Document Embeddings—0
Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation—0
Knowledge Graphs for Multilingual Language Translation and Generation—0
Reusing a Pretrained Language Model on Languages with Limited Corpora for Unsupervised NMTCode1
Combining Word and Character Vector Representation on Neural Machine Translation—0
Automatic Dialect Adaptation in Finnish and its Effect on Perceived CreativityCode1
Transformer based Multilingual document Embedding model—0
Very Deep Transformers for Neural Machine TranslationCode1
The Sockeye 2 Neural Machine Translation Toolkit at AMTA 2020—0
Revisiting Low Resource Status of Indian Languages in Machine Translation—0
Paraphrase Generation as Zero-Shot Multilingual Translation: Disentangling Semantic Similarity from Lexical and Syntactic DiversityCode1
Data Weighted Training Strategies for Grammatical Error Correction—0
Neural Machine Translation with Error CorrectionCode0
Neural Machine Translation model for University Email Application—0
CoCoNuT: Combining Context-Aware Neural Translation Models using Ensemble for Program RepairCode1
A Novel Graph-based Multi-modal Fusion Encoder for Neural Machine TranslationCode1
Dual Past and Future for Neural Machine Translation—0
Rewiring the Transformer with Depth-Wise LSTMs—0
Sequence Generation with Mixed RepresentationsCode1
Language-agnostic BERT Sentence EmbeddingCode1
Improving Autoregressive NMT with Non-Autoregressive Model—0
Efficient Neural Machine Translation for Low-Resource Languages via Exploiting Related Languages—0
NAIST's Machine Translation Systems for IWSLT 2020 Conversational Speech Translation Task—0
Octanove Labs' Japanese-Chinese Open Domain Translation System—0
Findings of the Fourth Workshop on Neural Generation and Translation—0
SIGMORPHON 2020 Task 0 System Description: ETH Z\"urich Team—0
The HW-TSC Video Speech Translation System at IWSLT 2020—0
Start-Before-End and End-to-End: Neural Speech Translation by AppTek and RWTH Aachen University—0
Checkpoint Reranking: An Approach to Select Better Hypothesis for Neural Machine Translation Systems—0
Compressing Neural Machine Translation Models with 4-bit Precision—0
HausaMT v1.0: Towards English--Hausa Neural Machine TranslationCode1
Improving Document-Level Neural Machine Translation with Domain Adaptation—0
Pre-training via Leveraging Assisting Languages for Neural Machine Translation—0
English-to-Japanese Diverse Translation by Combining Forward and Backward Outputs—0
FFR v1.1: Fon-French Neural Machine Translation—0
SimulSpeech: End-to-End Simultaneous Speech to Text Translation—0
Multi-Task Neural Model for Agglutinative Language Translation—0
Document Translation vs. Query Translation for Cross-Lingual Information Retrieval in the Medical Domain—0
Improving Neural Machine Translation with Soft Template Prediction—0
Language-aware Interlingua for Multilingual Neural Machine Translation—0
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