Dataset Card for "scientific_papers"

Dataset Summary

Scientific papers datasets contains two sets of long and structured documents. The datasets are obtained from ArXiv and PubMed OpenAccess repositories.

Both "arxiv" and "pubmed" have two features:

  • article: the body of the document, pagragraphs seperated by "/n".
  • abstract: the abstract of the document, pagragraphs seperated by "/n".
  • section_names: titles of sections, seperated by "/n".

Supported Tasks

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Languages

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Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

arxiv

  • Size of downloaded dataset files: 4295.97 MB
  • Size of the generated dataset: 7231.70 MB
  • Total amount of disk used: 11527.66 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "abstract": "\" we have studied the leptonic decay @xmath0 , via the decay channel @xmath1 , using a sample of tagged @xmath2 decays collected...",
    "article": "\"the leptonic decays of a charged pseudoscalar meson @xmath7 are processes of the type @xmath8 , where @xmath9 , @xmath10 , or @...",
    "section_names": "[sec:introduction]introduction\n[sec:detector]data and the cleo- detector\n[sec:analysys]analysis method\n[sec:conclusion]summary"
}

pubmed

  • Size of downloaded dataset files: 4295.97 MB
  • Size of the generated dataset: 2390.49 MB
  • Total amount of disk used: 6686.46 MB

An example of 'validation' looks as follows.

This example was too long and was cropped:

{
    "abstract": "\" background and aim : there is lack of substantial indian data on venous thromboembolism ( vte ) . \\n the aim of this study was...",
    "article": "\"approximately , one - third of patients with symptomatic vte manifests pe , whereas two - thirds manifest dvt alone .\\nboth dvt...",
    "section_names": "\"Introduction\\nSubjects and Methods\\nResults\\nDemographics and characteristics of venous thromboembolism patients\\nRisk factors ..."
}

Data Fields

The data fields are the same among all splits.

arxiv

  • article: a string feature.
  • abstract: a string feature.
  • section_names: a string feature.

pubmed

  • article: a string feature.
  • abstract: a string feature.
  • section_names: a string feature.

Data Splits Sample Size

name train validation test
arxiv 203037 6436 6440
pubmed 119924 6633 6658

Dataset Creation

Curation Rationale

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Source Data

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Annotations

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information


@article{Cohan_2018,
   title={A Discourse-Aware Attention Model for Abstractive Summarization of
            Long Documents},
   url={http://dx.doi.org/10.18653/v1/n18-2097},
   DOI={10.18653/v1/n18-2097},
   journal={Proceedings of the 2018 Conference of the North American Chapter of
          the Association for Computational Linguistics: Human Language
          Technologies, Volume 2 (Short Papers)},
   publisher={Association for Computational Linguistics},
   author={Cohan, Arman and Dernoncourt, Franck and Kim, Doo Soon and Bui, Trung and Kim, Seokhwan and Chang, Walter and Goharian, Nazli},
   year={2018}
}

Contributions

Thanks to @thomwolf, @jplu, @lewtun, @patrickvonplaten for adding this dataset.

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Models trained or fine-tuned on scientific_papers