Natural Language Generation (NLG) has improved exponentially in recent years thanks to
the development of sequence-to-sequence deep learning technologies such as Transformer …

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

We present a survey covering the state of the art in low-resource machine translation (MT)
research. There are currently around 7,000 languages spoken in the world and almost all …

In this work, we study hallucinations in Neural Machine Translation (NMT), which lie at an
extreme end on the spectrum of NMT pathologies. Firstly, we connect the phenomenon of …

The notion of" in-domain data" in NLP is often over-simplistic and vague, as textual data
varies in many nuanced linguistic aspects such as topic, style or level of formality. In …

We report on methods to create the largest publicly available parallel corpora by crawling
the web, using open source software. We empirically compare alternative methods and …

Neural sequence models can generate highly fluent sentences, but recent studies have also
shown that they are also prone to hallucinate additional content not supported by the input …

We frame the task of machine translation evaluation as one of scoring machine translation
output with a sequence-to-sequence paraphraser, conditioned on a human reference. We …

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