AraSum

This repository contains the AraSum corpus which is the first monolingual corpus in the Arabic language for abstractive text summarization. For details of how we created the corpus, please refer to our paper: Cross-lingual Fine-tuning for Abstractive Arabic Text Summarization published in the Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021).

We are releasing the AraSum corpus which is the first monolingual corpus for abstractive text summarization for the Arabic language. The AraSum corpus contains 49604 articles and their corresponding leads.

The source for AraSum corpus is the Arabic version of the Deutsche Welle DW news website. The downloaded items address a wide range of topics, not only dealing with politics, sports, or art. This allows the summary database to cover a wide range of topics, making more realistic testing of the capabilities of the summarization models as well as the creation of more robust and less domain-dependent models possible.

AraSum files are in .csv format one CSV per line each line contains an article TAB lead.

Citation:

If you use our corpus, please cite the following paper:

@inproceedings{kahla-etal-2021-cross,
    title = "Cross-lingual Fine-tuning for Abstractive {A}rabic Text Summarization",
    author = "Kahla, Mram  and
      Yang, Zijian Gy{\H{o}}z{\H{o}}  and
      Nov{\'a}k, Attila",
    booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)",
    month = sep,
    year = "2021",
    address = "Held Online",
    publisher = "INCOMA Ltd.",
    url = "https://aclanthology.org/2021.ranlp-1.74",
    pages = "655--663",
}