Neural sequence to sequence learning recently became a very promising
paradigm in machine translation, achieving competitive results with statistical
phrase-based systems. In this system description paper, we attempt to utilize
several recently published methods used for neural sequential learning in order
to build systems for WMT 2016 shared tasks of Automatic Post-Editing and
Multimodal Machine Translation.Comment: Accepted to the First Conference of Machine Translation (WMT16