metadata
license: apache-2.0
task_categories:
- summarization
language:
- en
pretty_name: PubMed-Lay
LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization
A collaboration between reciTAL, MLIA (ISIR, Sorbonne Université), Meta AI, and Università di Trento
PubMed-Lay dataset for summarization
PubMed-Lay is an enhanced version of the PubMed summarization dataset, for which layout information is provided.
Data Fields
article_id: article idarticle_words: sequence of words constituting the body of the articlearticle_bboxes: sequence of corresponding word bounding boxesnorm_article_bboxes: sequence of corresponding normalized word bounding boxesabstract: a string containing the abstract of the articlearticle_pdf_url: URL of the article's PDF
Data Splits
This dataset has 3 splits: train, validation, and test.
| Dataset Split | Number of Instances |
|---|---|
| Train | 78,234 |
| Validation | 4,084 |
| Test | 4,350 |
Citation
@article{nguyen2023loralay,
title={LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization},
author={Nguyen, Laura and Scialom, Thomas and Piwowarski, Benjamin and Staiano, Jacopo},
journal={arXiv preprint arXiv:2301.11312},
year={2023}
}