Publication:
UKP-SQUARE: an online platform for question answering research

dc.conference.dateMAY 22-27, 2022
dc.conference.locationDublin, Ireland
dc.conference.organizer60th Annual Meeting of the Association-for-Computational-Linguistics (ACL)
dc.contributor.coauthorBaumgaertner, Tim
dc.contributor.coauthorWang, Kexin
dc.contributor.coauthorSachdeva, Rachneet
dc.contributor.coauthorEichler, Max
dc.contributor.coauthorGeigle, Gregor
dc.contributor.coauthorPoth, Clifton
dc.contributor.coauthorSterz, Hannah
dc.contributor.coauthorPuerto, Haritz
dc.contributor.coauthorRibeiro, Leonardo F. R.
dc.contributor.coauthorPfeiffer, Jonas
dc.contributor.coauthorReimers, Nils
dc.contributor.coauthorGurevych, Iryna
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.facultymemberYes
dc.contributor.kuauthorŞahin, Gözde Gül
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2024-11-09T23:43:49Z
dc.date.issued2022
dc.description.abstractRecent advances in NLP and information retrieval have given rise to a diverse set of question answering tasks that are of different formats (e.g., extractive, abstractive), require different model architectures (e.g., generative, discriminative), and setups (e.g., with or without retrieval). Despite having a large number of powerful, specialized QA pipelines (which we refer to as Skills) that consider a single domain, model or setup, there exists no framework where users can easily explore and compare such pipelines and can extend them according to their needs. To address this issue, we present UKP-SQUARE, an extensible online QA platform for researchers which allows users to query and analyze a large collection of modern Skills via a user-friendly web interface and integrated behavioural tests. In addition, QA researchers can develop, manage, and share their custom Skills using our microservices that support a wide range of models (Transformers, Adapters, ONNX), data-stores and retrieval techniques (e.g., sparse and dense). UKP-SQUARE is available on https://square.ukp-lab.de.(1)
dc.description.fulltextNo
dc.description.harvestedfromManual
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.openaccessNO
dc.description.peerreviewstatusN/A
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsoredbyTubitakEuEU
dc.description.sponsorshipGerman Research Foundation (DFG) as part of the UKPSQuARE project [GU 798/29-1]
dc.description.sponsorshipDFG [GU 798/25-1, GU 798/18-3, GRK 1994/1]
dc.description.sponsorshipEuropean Regional Development Fund (ERDF)
dc.description.sponsorshipHessian State Chancellery-Hessian Minister of Digital Strategy and Development [20005482]
dc.description.sponsorshipLOEWE initiative (Hesse, Germany) within the emergenCITY center
dc.description.sponsorshipPriority Program "Robust Argumentation Machines (RATIO)" (SPP-1999) This work has been funded by: (i) the German Research Foundation (DFG) as part of the UKPSQuARE project (grant GU 798/29-1), (ii) the DFG as part of the QASciInf project (GU 798/18-3), (iii) the DFG within the project "Open Argument Mining" (GU 798/25-1), associated with the Priority Program "Robust Argumentation Machines (RATIO)" (SPP-1999), (iv) the DFG-funded research training group "Adaptive Preparation of Information form Heterogeneous Sources" (AIPHES, GRK 1994/1), (v) the European Regional Development Fund (ERDF) and the Hessian State Chancellery-Hessian Minister of Digital Strategy and Development under the promotional reference 20005482 (TexPrax), and (vi) the LOEWE initiative (Hesse, Germany) within the emergenCITY center.
dc.description.studentonlypublicationNo
dc.description.studentpublicationNo
dc.description.versionN/A
dc.identifier.WoSQuartileN/A
dc.identifier.doi10.48550/arXiv.2203.13693
dc.identifier.eissnN/A
dc.identifier.embargoN/A
dc.identifier.endpage22
dc.identifier.grantnoGU 798/29-1
dc.identifier.grantnoGU 798/25-1
dc.identifier.grantnoGU 798/18-3
dc.identifier.grantnoGRK 1994/1
dc.identifier.grantno20005482
dc.identifier.isbn9781955917247
dc.identifier.issnN/A
dc.identifier.scopus2-s2.0-85149107654
dc.identifier.startpage9
dc.identifier.urihttps://doi.org/10.48550/arXiv.2203.13693
dc.identifier.urihttps://hdl.handle.net/20.500.14288/13559
dc.identifier.wos000828759800002
dc.keywordsBehavioural tests
dc.keywordsComputational linguistics
dc.keywordsHTTP
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.ispartofProceedings of The 60th Annual Meeting of The Association for Computational Linguistics (ACL 2022): Proceedings of System Demonstrations
dc.relation.openaccessN/A
dc.rightsN/A
dc.subjectComputer Science
dc.subjectArtificial intelligence
dc.subjectLinguistics
dc.titleUKP-SQUARE: an online platform for question answering research
dc.typeConference Proceeding
dspace.entity.typePublication
local.contributor.kuauthorŞahin, Gözde Gül
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relation.isOrgUnitOfPublication.latestForDiscovery89352e43-bf09-4ef4-82f6-6f9d0174ebae
relation.isParentOrgUnitOfPublication8e756b23-2d4a-4ce8-b1b3-62c794a8c164
relation.isParentOrgUnitOfPublication.latestForDiscovery8e756b23-2d4a-4ce8-b1b3-62c794a8c164

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