nglaura/pubmedlay-summarization

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 id
• —article_words: sequence of words constituting the body of the article
• —article_bboxes: sequence of corresponding word bounding boxes
• —norm_article_bboxes: sequence of corresponding normalized word bounding boxes
• —abstract: a string containing the abstract of the article
• —article_pdf_url: URL of the article's PDF

Data Splits

This dataset has 3 splits: train, validation, and test.

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}
}