Neural Machine Translation (NMT) has seen tremendous growth in the last ten years since
the early 2000s and has already entered a mature phase. While considered the most widely …

Abstract Evaluation practices in natural language generation (NLG) have many known flaws,
but improved evaluation approaches are rarely widely adopted. This issue has become …

Driven by the goal of eradicating language barriers on a global scale, machine translation
has solidified itself as a key focus of artificial intelligence research today. However, such …

Existing work in translation demonstrated the potential of massively multilingual machine
translation by training a single model able to translate between any pair of languages …

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 …

We present an approach based on multilingual sentence embeddings to automatically
extract parallel sentences from the content of Wikipedia articles in 85 languages, including …

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 show that margin-based bitext mining in a multilingual sentence space can be applied to
monolingual corpora of billions of sentences. We are using ten snapshots of a curated …