  This document describes the findings of the Third Workshop on Neural
Generation and Translation, held in concert with the annual conference of the
Empirical Methods in Natural Language Processing (EMNLP 2019). First, we
summarize the research trends of papers presented in the proceedings. Second,
we describe the results of the two shared tasks 1) efficient neural machine
translation (NMT) where participants were tasked with creating NMT systems that
are both accurate and efficient, and 2) document-level generation and
translation (DGT) where participants were tasked with developing systems that
generate summaries from structured data, potentially with assistance from text
in another language.
