Neural machine translation, a recently proposed approach to machine translation based
purely on neural networks, has shown promising results compared to the existing …

Common recurrent neural architectures scale poorly due to the intrinsic difficulty in
parallelizing their state computations. In this work, we propose the Simple Recurrent Unit …

This paper presents the results of the WMT14 shared tasks, which included a standard news
translation task, a separate medical translation task, a task for run-time estimation of …

Common recurrent neural network architectures scale poorly due to the intrinsic difficulty in
parallelizing their state computations. In this work, we propose the Simple Recurrent Unit …

The amount of time required to train a neural network may be decreased by modifying the
neural network to allow for greater parallelization of computations. The computations for …

This paper describes one of the collaborative efforts within EU-BRIDGE to further advance
the state of the art in machine translation between two European language pairs, German→ …

This paper describes the statistical machine translation system developed at RWTH Aachen
University for the German→ English translation task of the EMNLP 2015 Tenth Workshop on …

The amount of time required to train a neural network may be decreased by modifying the
neural network to allow for greater parallelization of computations. The computations for …

Abstract Machine translation is a task in the field of natural language processing whose
objective is to translate documents from one human language into another human language …

Hierarchical phrase-based translation is a common machine translation approach for
translating between languages with significantly different word order. The focus of the first …