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README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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task_categories:
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- text-generation
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language:
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- en
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size_categories:
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- 10K<n<100K
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---
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# Raw Review Dataset for [Reviewer2](https://arxiv.org/abs/2402.10886)
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This is the raw version of our dataset. The cleaned data files that can be directly used for fine-tuning is in [this](https://huggingface.co/datasets/GitBag/Reviewer2_PGE_cleaned) directory.
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## Dataset Structure
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The folders are structured in the following way:
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```
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venue
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|--venue_year
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|--venue_year_metadata
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|--venue_year_id1_metadata.json
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|--venue_year_id2_metadata.json
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...
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|--venue_year_paper
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|--venue_year_id1_paper.json
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|--venue_year_id2_paper.json
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...
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|--venue_year_review
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|--venue_year_id1_review.json
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|--venue_year_id2_review.json
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...
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|--venue_year_pdf
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|--venue_year_id1_pdf.pdf
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|--venue_year_id2_pdf.pdf
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...
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```
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## Dataset Content
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#### Paper Contents
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- title: title of the paper
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- authors: list of author names
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- emails: list of author emails
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- sections: list of sections of the paper
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- heading: heading of the section
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- text: text of the section
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- references: list of references of the paper
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- title: title of the reference
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- author: list of author names of the reference
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- venue: venue of the reference
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- citeRegEx: citation expression
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- shortCiteRegEx: short citation expression
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- year: publication year of the reference
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- referenceMentions: the location of the reference
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in the paper
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- referenceID: numerical reference id
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- context: context of the reference in the paper
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- startOffset: start index of the context
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- endOffset: end index of the context
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- year: year of publication
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- abstractText: abstract of the paper
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#### Metadata Contents
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- id: unique id of the paper
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- conference: venue for the paper
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- decision: final decision for the paper (accept/reject)
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- url: link to the PDF of the paper
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- review_url: link to the review of the paper
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- title: title of the paper
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- authors: list of the authors of the paper
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## Dataset Sources
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We incorporate parts of the [PeerRead](https://github.com/allenai/PeerRead) and [NLPeer](https://github.com/UKPLab/nlpeer) datasets along with an update-to-date crawl from ICLR and NeurIPS on [OpenReview](https://openreview.net/) and [NeurIPS Proceedings](http://papers.neurips.cc/).
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## Citation
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If you find this dataset useful in your research, please cite the following paper:
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```
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@misc{gao2024reviewer2,
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title={Reviewer2: Optimizing Review Generation Through Prompt Generation},
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author={Zhaolin Gao and Kianté Brantley and Thorsten Joachims},
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year={2024},
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eprint={2402.10886},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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