NLPEERv2: A Unified Resource for the Computational Study of Peer Review

datacite.relation.isDerivedFrom https://aclanthology.org/2023.acl-long.277/
datacite.relation.isDerivedFrom https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2495
datacite.relation.isDerivedFrom https://doi.org/10.18150/FKPEQN
datacite.relation.isDerivedFrom https://doi.org/10.18150/KZHVGE
datacite.relation.isNewVersionOf https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3618
dc.contributor.author Dycke, Nils
dc.contributor.author Sheng, Lu
dc.contributor.author Holtdirk, Hanna
dc.contributor.author Gurevych, Iryna
dc.date.accessioned 2025-02-07T10:05:46Z
dc.date.available 2025-02-07T10:05:46Z
dc.date.created 2025-02
dc.date.issued 2025-02-07
dc.description Dataset of peer review reports and paper drafts from diverse domains and venues. It extends the previous dataset NLPEER to version 2. We provide all sub-versions of the dataset here (check the version tags). In doubt, select the newest one. We provide subsets of the dataset for ease of loading depending on your needs. For the accompanying code to load the data check: https://github.com/UKPLab/nlpeer. ARR-2024 got updated to version 1.1 -- it now also includes camera-ready versions of findings papers. de_DE
dc.description.version 1 de_DE
dc.identifier.uri https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4459
dc.language.iso en de_DE
dc.rights.licenseCC-BY-NC-4.0 (https://creativecommons.org/licenses/by-nc/4.0)
dc.subject peer review de_DE
dc.subject nlp for peer review de_DE
dc.subject arr de_DE
dc.subject acl de_DE
dc.subject.classification 4.43-04
dc.subject.classification 4.43-05
dc.subject.ddc 004
dc.title NLPEERv2: A Unified Resource for the Computational Study of Peer Review de_DE
dc.type Text de_DE
dcterms.accessRights restrictedAccess
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tuda.unit TUDa

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