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

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Files

nlpeer_v0.1.zip (NLPeer v0.1 Dataset) (13.15 GB)
 nlpeer_v0.1_nopdf.zip (NLPeer v0.1 Dataset w/o PDFS (for quick downloading if you only need parsed papers and reviews)) (500.32 MB)
 nlpeer_v0.zip (v0 of the dataset) (13.14 GB)
 nlpeer_v0_nopdf.zip (NLPeer v0 Dataset w/o PDFS (for quick downloading if you only need parsed papers and reviews)) (488.74 MB)

Date

2022-11-11

Type

Dataset

Authors

Dycke, Nils
Kuznetsov, Ilia
Gurevych, Iryna

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Description

Dataset of peer review reports and paper drafts from diverse domains and venues. We provide multiple versions of the dataset; when in doubt, download the newest version. You can also download a small-sized version without paper PDFs, in case you are fine with parsed papers and/or only need the peer review data. There is a new updated version NLPEERv2 available which includes additional data: https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4459 Change log: * v.0.1: includes splits and annotations for the NLPeer assistance tasks; we fixed minor text encoding issues for the PeerRead portion

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Citation

Identifier

https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3618
 https://doi.org/10.48328/tudatalib-979

Endorsement

Related Resources

Is Supplement To
https://aclanthology.org/2023.acl-long.277/

DFG Classification

4.43-04 Künstliche Intelligenz und Maschinelle Lernverfahren
4.43-05 Bild- und Sprachverarbeitung, Computergraphik und Visualisierung, Human Computer Interaction, Ubiquitous und Wearable Computing

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License

CC-BY-NC 4.0 - Attribution-NonCommercial 4.0 International
Except where otherwise noted, this license is described as CC-BY-NC 4.0 - Attribution-NonCommercial 4.0 International