Findings of the Third Workshop on Neural Generation and Translation
This is an incremental workshop report for the NLP community, documenting progress in neural generation and translation tasks.
The paper reports on the Third Workshop on Neural Generation and Translation, summarizing research trends and results from two shared tasks: efficient neural machine translation (focused on accuracy and efficiency) and document-level generation and translation (focused on generating summaries from structured data).
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.