Datasets:
scientific_papers

	---
	annotations_creators:
	- found
	language:
	- en
	language_creators:
	- found
	license:
	- unknown
	multilinguality:
	- monolingual
	pretty_name: ScientificPapers
	size_categories:
	- 100K<n<1M
	source_datasets:
	- original
	task_categories:
	- summarization
	task_ids: []
	paperswithcode_id: null
	tags:
	- abstractive-summarization
	dataset_info:
	- config_name: arxiv
	features:
	- name: article
	dtype: string
	- name: abstract
	dtype: string
	- name: section_names
	dtype: string
	splits:
	- name: train
	num_bytes: 7148341992
	num_examples: 203037
	- name: validation
	num_bytes: 217125524
	num_examples: 6436
	- name: test
	num_bytes: 217514961
	num_examples: 6440
	download_size: 4504646347
	dataset_size: 7582982477
	- config_name: pubmed
	features:
	- name: article
	dtype: string
	- name: abstract
	dtype: string
	- name: section_names
	dtype: string
	splits:
	- name: train
	num_bytes: 2252027383
	num_examples: 119924
	- name: validation
	num_bytes: 127403398
	num_examples: 6633
	- name: test
	num_bytes: 127184448
	num_examples: 6658
	download_size: 4504646347
	dataset_size: 2506615229
	---

	# Dataset Card for "scientific_papers"

	## Table of Contents
	- [Dataset Description](#dataset-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Annotations](#annotations)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Social Impact of Dataset](#social-impact-of-dataset)
	- [Discussion of Biases](#discussion-of-biases)
	- [Other Known Limitations](#other-known-limitations)
	- [Additional Information](#additional-information)
	- [Dataset Curators](#dataset-curators)
	- [Licensing Information](#licensing-information)
	- [Citation Information](#citation-information)
	- [Contributions](#contributions)

	## Dataset Description

	- Homepage:
	- Repository: https://github.com/armancohan/long-summarization
	- Paper: [A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents](https://arxiv.org/abs/1804.05685)
	- Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
	- Size of downloaded dataset files: 9.01 GB
	- Size of the generated dataset: 10.09 GB
	- Total amount of disk used: 19.10 GB

	### 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, paragraphs separated by "/n".
	- abstract: the abstract of the document, paragraphs separated by "/n".
	- section_names: titles of sections, separated by "/n".

	### Supported Tasks and Leaderboards

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Languages

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	## Dataset Structure

	### Data Instances

	#### arxiv

	- Size of downloaded dataset files: 4.50 GB
	- Size of the generated dataset: 7.58 GB
	- Total amount of disk used: 12.09 GB

	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: 4.50 GB
	- Size of the generated dataset: 2.51 GB
	- Total amount of disk used: 7.01 GB

	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

	\| name \|train \|validation\|test\|
	\|------\|-----:\|---------:\|---:\|
	\|arxiv \|203037\| 6436\|6440\|
	\|pubmed\|119924\| 6633\|6658\|

	## Dataset Creation

	### Curation Rationale

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Source Data

	#### Initial Data Collection and Normalization

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	#### Who are the source language producers?

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Annotations

	#### Annotation process

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	#### Who are the annotators?

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Personal and Sensitive Information

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	## Considerations for Using the Data

	### Social Impact of Dataset

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Discussion of Biases

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Other Known Limitations

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	## Additional Information

	### Dataset Curators

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### Licensing Information

	[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

	### 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](https://github.com/thomwolf), [@jplu](https://github.com/jplu), [@lewtun](https://github.com/lewtun), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.