In recent years, neural encoder-decoder models (Kalchbrenner and Blunsom, 2013; have significantly advanced the state of the art in NMT, and now consistently outperform Statistical Machine Translation (SMT) (Bojar et al., 2016).
their success hinges on the availability of sufficient amounts of parallel data, and contrary to the long line of research in SMT, there has only been a limited amount of work on how to effectively and efficiently make use of monolingual data which is typically amply available.