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 …

In recent years, natural language processing (NLP) has got great development with deep
learning techniques. In the sub-field of machine translation, a new approach named Neural …

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 …

With the development of high computational devices, deep neural networks (DNNs), in
recent years, have gained significant popularity in many Artificial Intelligence (AI) …

We propose an efficient method to generate white-box adversarial examples to trick a
character-level neural classifier. We find that only a few manipulations are needed to greatly …

We introduce our efforts towards building a universal neural machine translation (NMT)
system capable of translating between any language pair. We set a milestone towards this …

Neural Machine Translation (NMT) is an end-to-end learning approach for automated
translation, with the potential to overcome many of the weaknesses of conventional phrase …

Neural machine translation (NMT) offers a novel alternative formulation of translation that is
potentially simpler than statistical approaches. However to reach competitive performance …

Most existing machine translation systems operate at the level of words, relying on explicit
segmentation to extract tokens. We introduce a neural machine translation (NMT) model that …

Evaluating on adversarial examples has become a standard procedure to measure
robustness of deep learning models. Due to the difficulty of creating white-box adversarial …