---
license: apache-2.0
task_categories:
- summarization
language:
- en
pretty_name: arXiv-Lay
---

# LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization 

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/)

## Arxiv-Lay dataset for summarization

ArXiv-Lay is an enhanced version of the arXiv 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_. \

| Dataset Split | Number of Instances |
| ------------- | --------------------|
| Train         | 122,189             |
| Validation    | 4,374               |
| Test          | 4,356              |


## Citation

``` latex
@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}
}
```