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Dataset Card for peer_read
Dataset Summary
PearRead is a dataset of scientific peer reviews available to help researchers study this important artifact. The dataset consists of over 14K paper drafts and the corresponding accept/reject decisions in top-tier venues including ACL, NIPS and ICLR, as well as over 10K textual peer reviews written by experts for a subset of the papers.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
en-English
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
parsed_pdfs
name
:string
Filename in the datasetmetadata
:dict
Paper metadatasource
:string
Paper sourceauthors
:list<string>
List of paper authorstitle
:string
Paper titlesections
:list<dict>
List of section heading and corresponding descriptionheading
:string
Section headingtext
:string
Section description
references
:string
List of referencestitle
:string
Title of reference paperauthor
:list<string>
List of reference paper authorsvenue
:string
Reference venueciteRegEx
:string
Reference citeRegExshortCiteRegEx
:string
Reference shortCiteRegExyear
:int
Reference publish year
referenceMentions
:list<string>
List of reference mentionsreferenceID
:int
Reference mention IDcontext
:string
Reference mention contextstartOffset
:int
Reference startOffsetendOffset
:int
Reference endOffset
year
:int
Paper publish yearabstractText
:string
Paper abstractcreator
:string
Paper creator
reviews
id
:int
Review IDconference
:string
Conference namecomments
:string
Review commentssubjects
:string
Review subjectsversion
:string
Review versiondate_of_submission
:string
Submission datetitle
:string
Paper titleauthors
:list<string>
List of paper authorsaccepted
:bool
Paper accepted flagabstract
:string
Paper abstracthistories
:list<string>
Paper details with linkreviews
:dict
Paper reviewsdate
:string
Date of reviewtitle
:string
Paper titleother_keys
:string
Reviewer other detailsoriginality
:string
Originality scorecomments
:string
Reviewer commentsis_meta_review
:bool
Review type flagrecommendation
:string
Reviewer recommendationreplicability
:string
Replicability scorepresentation_format
:string
Presentation typeclarity
:string
Clarity scoremeaningful_comparison
:string
Meaningful comparison scoresubstance
:string
Substance scorereviewer_confidence
:string
Reviewer confidence scoresoundness_correctness
:string
Soundness correctness scoreappropriateness
:string
Appropriateness scoreimpact
:string
Impact score
Data Splits
[More Information Needed]
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
Dongyeop Kang, Waleed Ammar, Bhavana Dalvi Mishra, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard Hovy, Roy Schwartz
Licensing Information
[More Information Needed]
Citation Information
@inproceedings{kang18naacl, title = {A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications}, author = {Dongyeop Kang and Waleed Ammar and Bhavana Dalvi and Madeleine van Zuylen and Sebastian Kohlmeier and Eduard Hovy and Roy Schwartz}, booktitle = {Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL)}, address = {New Orleans, USA}, month = {June}, url = {https://arxiv.org/abs/1804.09635}, year = {2018} }
Contributions
Thanks to @vinaykudari for adding this dataset.
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