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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
SciELO dataset for summarization
SciELO is a dataset for summarization of research papers written in Spanish and Portuguese, 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 (ES/PT) |
|---|---|
| Train | 20,853 / 19,407 |
| Validation | 1,158 / 1,078 |
| Test | 1,159 / 1,078 |
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}
}
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