Findings of the Third Workshop on Neural Generation and Translation

TL;DR

This paper summarizes research trends and shared task results from the Third Workshop on Neural Generation and Translation at EMNLP 2019, focusing on efficient neural machine translation and document-level generation and translation.

Contribution

It provides an overview of current research directions and presents results from shared tasks on efficient NMT and document-level generation and translation.

Findings

Summarized research trends in neural generation and translation.

Reported results from shared tasks on efficient NMT and DGT.

Highlighted advancements in neural generation techniques.

Abstract

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.