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Why neural translations are the right length

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dc.contributor.coauthorShi, Xing
dc.contributor.coauthorKnight, Kevin
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.facultymemberYes
dc.contributor.kuauthorYüret, Deniz
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2024-11-09T23:36:41Z
dc.date.issued2016
dc.description.abstractWe investigate how neural, encoder-decoder translation systems output target strings of appropriate lengths, finding that a collection of hidden units learns to explicitly implement this functionality.
dc.description.fulltextNo
dc.description.harvestedfromManual
dc.description.indexedbyScopus
dc.description.openaccessYES
dc.description.peerreviewstatusN/A
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipAmazon.com
dc.description.sponsorshipBaidu
dc.description.sponsorshipet al.
dc.description.sponsorshipGoogle
dc.description.sponsorshipGrammarly
dc.description.sponsorshipMicrosoft
dc.description.versionN/A
dc.identifier.doi10.18653/v1/d16-1248
dc.identifier.embargoN/A
dc.identifier.isbn9781-9456-2625-8
dc.identifier.quartileBakılacak
dc.identifier.scopus2-s2.0-85029504200
dc.identifier.urihttps://doi.org/10.18653/v1/d16-1248
dc.identifier.urihttps://hdl.handle.net/20.500.14288/12688
dc.keywordsTranslation (languages)
dc.keywordsEncoder-decoder
dc.keywordsHidden units
dc.keywordsTranslation systems
dc.keywordsNatural language processing systems
dc.language.isoeng
dc.publisherAssociation for Computational Linguistics (ACL)
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofEMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings
dc.relation.openaccessN/A
dc.rightsN/A
dc.subjectComputer engineering
dc.titleWhy neural translations are the right length
dc.typeConference Proceeding
dspace.entity.typePublication
local.contributor.kuauthorYüret, Deniz
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relation.isOrgUnitOfPublication.latestForDiscovery89352e43-bf09-4ef4-82f6-6f9d0174ebae
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