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 WMT17 shared tasks, which included three machine
translation (MT) tasks (news, biomedical, and multimodal), two evaluation tasks (metrics and …

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 …

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 …

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

Cross-lingual document alignment aims to identify pairs of documents in two distinct
languages that are of comparable content or translations of each other. In this paper, we …

Progress in sentence simplification has been hindered by a lack of labeled parallel
simplification data, particularly in languages other than English. We introduce MUSS, a …

Judging the safety of a URL is something that even security experts struggle to do accurately
without additional information. In this work, we aim to make experts' tools accessible to non …