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Findings of the Fourth Workshop on Neural Generation and Translation

Kenneth Heafield, Hiroaki Hayashi, Yusuke Oda, Ioannis Konstas, Andrew Finch, Graham Neubig, Xian Li, Alexandra Birch

202025 citationsDOIOpen Access PDF

Abstract

We describe the finding of the Fourth Workshop on Neural Generation and Translation, held in concert with the annual conference of the Association for Computational Linguistics (ACL 2020). First, we summarize the research trends of papers presented in the proceedings. Second, we describe the results of the three 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 and 3) STAPLE task: creation of as many possible translations of a given input text. This last shared task was organised by Duolingo.

Topics & Concepts

Machine translationComputer scienceTask (project management)Natural language processingText generationArtificial intelligenceComputational linguisticsTranslation (biology)EngineeringGeneBiochemistrySystems engineeringMessenger RNAChemistryNatural Language Processing TechniquesTopic ModelingMultimodal Machine Learning Applications
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