README.md

metadata

license: apache-2.0
task_categories:
  - summarization
language:
  - en
pretty_name: PeerSum
size_categories:
  - 10K<n<100K

This is PeerSum, a multi-document summarization dataset in the peer-review domain. More details can be found in the paper accepted at EMNLP 2023, Summarizing Multiple Documents with Conversational Structure for Meta-review Generation. The original code and datasets are public on GitHub.

Please use the following code to download the dataset with the datasets library from Huggingface.

from datasets import load_dataset
# peersum_all = load_dataset('oaimli/PeerSum', split='all')
# peersum_train = peersum_all.filter(lambda s: s['label'] == 'train')
# peersum_val = peersum_all.filter(lambda s: s['label'] == 'val')
# peersum_test = peersum_all.filter(lambda s: s['label'] == 'test')

You can also download the raw data from Google Drive. The raw data comprises more information and it can be used for other analysis for peer reviews.