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--- |
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license: apache-2.0 |
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task_categories: |
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- summarization |
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language: |
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- fr |
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pretty_name: SciELO |
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--- |
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# LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization |
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A collaboration between [reciTAL](https://recital.ai/en/), [MLIA](https://mlia.lip6.fr/) (ISIR, Sorbonne Université), [Meta AI](https://ai.facebook.com/), and [Università di Trento](https://www.unitn.it/) |
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## SciELO dataset for summarization |
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SciELO is a dataset for summarization of research papers written in Spanish and Portuguese, for which layout information is provided. |
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### Data Fields |
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- `article_id`: article id |
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- `article_words`: sequence of words constituting the body of the article |
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- `article_bboxes`: sequence of corresponding word bounding boxes |
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- `norm_article_bboxes`: sequence of corresponding normalized word bounding boxes |
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- `abstract`: a string containing the abstract of the article |
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- `article_pdf_url`: URL of the article's PDF |
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### Data Splits |
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This dataset has 3 splits: _train_, _validation_, and _test_. |
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| Dataset Split | Number of Instances (ES/PT) | |
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| ------------- | ----------------------------| |
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| Train | 20,853 / 19,407 | |
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| Validation | 1,158 / 1,078 | |
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| Test | 1,159 / 1,078 | |
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## Citation |
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``` latex |
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@article{nguyen2023loralay, |
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title={LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization}, |
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author={Nguyen, Laura and Scialom, Thomas and Piwowarski, Benjamin and Staiano, Jacopo}, |
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journal={arXiv preprint arXiv:2301.11312}, |
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year={2023} |
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} |
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``` |
