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Microsoft Translator at WMT 2019: Towards Large-Scale Document-Level Neural Machine Translation
This paper describes the Microsoft Translator submissions to the WMT19 n...
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Dual Conditional Cross-Entropy Filtering of Noisy Parallel Corpora
In this work we introduce dual conditional cross-entropy filtering for n...
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Microsoft's Submission to the WMT2018 News Translation Task: How I Learned to Stop Worrying and Love the Data
This paper describes the Microsoft submission to the WMT2018 news transl...
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MS-UEdin Submission to the WMT2018 APE Shared Task: Dual-Source Transformer for Automatic Post-Editing
This paper describes the Microsoft and University of Edinburgh submissio...
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Accelerating Asynchronous Stochastic Gradient Descent for Neural Machine Translation
In order to extract the best possible performance from asynchronous stoc...
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Marian: Cost-effective High-Quality Neural Machine Translation in C++
This paper describes the submissions of the "Marian" team to the WNMT 20...
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Near Human-Level Performance in Grammatical Error Correction with Hybrid Machine Translation
We combine two of the most popular approaches to automated Grammatical E...
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Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task
Previously, neural methods in grammatical error correction (GEC) did not...
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Marian: Fast Neural Machine Translation in C++
We present Marian, an efficient and self-contained Neural Machine Transl...
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Achieving Human Parity on Automatic Chinese to English News Translation
Machine translation has made rapid advances in recent years. Millions of...
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An Exploration of Neural Sequence-to-Sequence Architectures for Automatic Post-Editing
In this work, we explore multiple neural architectures adapted for the t...
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Nematus: a Toolkit for Neural Machine Translation
We present Nematus, a toolkit for Neural Machine Translation. The toolki...
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Predicting Target Language CCG Supertags Improves Neural Machine Translation
Neural machine translation (NMT) models are able to partially learn synt...
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Fast, Scalable Phrase-Based SMT Decoding
The utilization of statistical machine translation (SMT) has grown enorm...
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Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions
In this paper we provide the largest published comparison of translation...
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Target-Side Context for Discriminative Models in Statistical Machine Translation
Discriminative translation models utilizing source context have been sho...
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Phrase-based Machine Translation is State-of-the-Art for Automatic Grammatical Error Correction
In this work, we study parameter tuning towards the M^2 metric, the stan...
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The AMU-UEDIN Submission to the WMT16 News Translation Task: Attention-based NMT Models as Feature Functions in Phrase-based SMT
This paper describes the AMU-UEDIN submissions to the WMT 2016 shared ta...
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Log-linear Combinations of Monolingual and Bilingual Neural Machine Translation Models for Automatic Post-Editing
This paper describes the submission of the AMU (Adam Mickiewicz Universi...
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