Machine translation (MT) is an important task in natural language processing (NLP), as it
automates the translation process and reduces the reliance on human translators. With the …

The quality of human translation was long thought to be unattainable for computer
translation systems. In this study, we present a deep-learning system, CUBBITT, which …

This paper presents the results of the premier shared task organized alongside the
Conference on Machine Translation (WMT) 2019. Participants were asked to build machine …

Abstract Machine translation (MT) is a technique that leverages computers to translate
human languages automatically. Nowadays, neural machine translation (NMT) which …

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 …

This paper presents the results of the news translation task, the multilingual low-resource
translation for Indo-European languages, the triangular translation task, and the automatic …

The quality of machine translation has increased remarkably over the past years, to the
degree that it was found to be indistinguishable from professional human translation in a …

There has been a growing interest in developing multimodal machine translation (MMT)
systems that enhance neural machine translation (NMT) with visual knowledge. This …

Standard automatic metrics, eg BLEU, are not reliable for document-level MT evaluation.
They can neither distinguish document-level improvements in translation quality from …

In this work, we train an Automatic Post-Editing (APE) model and use it to reveal biases in
standard Machine Translation (MT) evaluation procedures. The goal of our APE model is to …