After more than 70 years of evolution, great achievements have been made in machine
translation. Especially in recent years, translation quality has been greatly improved with the …

The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …

This paper presents the results of the WMT17 shared tasks, which included three machine
translation (MT) tasks (news, biomedical, and multimodal), two evaluation tasks (metrics and …

The extraction of labels from radiology text reports enables large-scale training of medical
imaging models. Existing approaches to report labeling typically rely either on sophisticated …

Recent work in Neural Machine Translation (NMT) has shown significant quality gains from
noised-beam decoding during back-translation, a method to generate synthetic parallel …

In this work, we examine methods for data augmentation for text-based tasks such as neural
machine translation (NMT). We formulate the design of a data augmentation policy with …

The development of deep learning techniques has allowed Neural Machine Translation
(NMT) models to become extremely powerful, given sufficient training data and training time …

Abstract Machine translation (MT) is an important sub-field of natural language processing
that aims to translate natural languages using computers. In recent years, end-to-end neural …

This work presents an empirical approach to quantifying the loss of lexical richness in
Machine Translation (MT) systems compared to Human Translation (HT). Our experiments …

The main barrier to progress in the task of Formality Style Transfer is the inadequacy of
training data. In this paper, we study how to augment parallel data and propose novel and …