Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
License:
license: apache-2.0 | |
task_categories: | |
- text-generation | |
language: | |
- en | |
size_categories: | |
- 10K<n<100K | |
# Cleaned Review Dataset for [Reviewer2](https://arxiv.org/abs/2402.10886) | |
This is a cleaned version of our dataset and can be directly used for fine-tuning. The raw data files including metadata for each paper is in [this](https://huggingface.co/datasets/GitBag/Reviewer2_PGE_raw/) directory. | |
- **venue:** venue of the paper; | |
- **paper_content:** content of the paper divided into sections | |
- **prompt:** prompt generated for the review based on our PGE pipeline | |
- **format:** the format of the review | |
- **review:** human-written review for the paper | |
## Dataset Sources | |
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/). | |
## Citation | |
If you find this dataset useful in your research, please cite the following paper: | |
``` | |
@misc{gao2024reviewer2, | |
title={Reviewer2: Optimizing Review Generation Through Prompt Generation}, | |
author={Zhaolin Gao and Kianté Brantley and Thorsten Joachims}, | |
year={2024}, | |
eprint={2402.10886}, | |
archivePrefix={arXiv}, | |
primaryClass={cs.CL} | |
} | |
``` |