  This document describes the findings of the Second Workshop on Neural Machine
Translation and Generation, held in concert with the annual conference of the
Association for Computational Linguistics (ACL 2018). First, we summarize the
research trends of papers presented in the proceedings, and note that there is
particular interest in linguistic structure, domain adaptation, data
augmentation, handling inadequate resources, and analysis of models. Second, we
describe the results of the workshop's shared task on efficient neural machine
translation, where participants were tasked with creating MT systems that are
both accurate and efficient.
