---
license: apache-2.0
tags:
- Automated Peer Reviewing
- SFT
- Dataset
---

## Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis

Paper Link: https://arxiv.org/abs/2407.12857

Project Page: https://ecnu-sea.github.io/


## Dataset Details

Each dataset contains four types of files as follows:

- **paper_raw_pdf:** Original paper in PDF format.
- **paper_nougat_mmd:** The mmd files after parsed by [Nougat](https://github.com/facebookresearch/nougat).
- **review_raw_txt:** Crawled raw review text.
- **review_json:** The processed review JSON file, including “Decision”, “Meta Review”, and for each review, “Summary”, “Strengths”, “Weaknesses”, “Questions”, “Soundness”, “Presentation”, “Contribution”, “Confidence”, and “Rating”.


## Dataset Sources

We crawl the latest papers and their corresponding reviews from [OpenReview](https://openreview.net), including NeurIPS-2023 and ICLR-2024.



## Citation

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

If you find our paper or models helpful, please consider cite as follows:

```bibtex
@inproceedings{yu2024automated,
  title={Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis},
  author={Yu, Jianxiang and Ding, Zichen and Tan, Jiaqi and Luo, Kangyang and Weng, Zhenmin and Gong, Chenghua and Zeng, Long and Cui, RenJing and Han, Chengcheng and Sun, Qiushi and others},
  booktitle={Findings of the Association for Computational Linguistics: EMNLP 2024},
  pages={10164--10184},
  year={2024}
}
```