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---
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annotations_creators:
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- found
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language:
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- en
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language_creators:
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- found
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license:
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- unknown
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multilinguality:
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- monolingual
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pretty_name: ScientificPapers
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size_categories:
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- 100K<n<1M
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source_datasets:
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- scientific_papers
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task_categories:
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- summarization
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task_ids: []
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paperswithcode_id: null
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tags:
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- abstractive-summarization
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dataset_info:
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- config_name: arxiv
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features:
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- name: article
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dtype: string
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- name: abstract
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dtype: string
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- name: section_names
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dtype: string
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splits:
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- name: train
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num_bytes: 7148341992
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num_examples: 203037
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- name: validation
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num_bytes: 217125524
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num_examples: 6436
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- name: test
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num_bytes: 217514961
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num_examples: 6440
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download_size: 4504646347
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dataset_size: 7582982477
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---
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# Dataset Card for "scientific_papers"
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Homepage:**
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- **Repository:** https://github.com/armancohan/long-summarization
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- **Paper:** [A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents](https://arxiv.org/abs/1804.05685)
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- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Dataset Summary
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Scientific papers datasets contains one sets of long and structured documents.
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The datasets are obtained from ArXiv repositories.
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### Supported Tasks and Leaderboards
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Languages
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Dataset Structure
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### Data Instances
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#### arxiv
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- **Size of downloaded dataset files:** 4.50 GB
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- **Size of the generated dataset:** 7.58 GB
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- **Total amount of disk used:** 12.09 GB
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An example of 'train' looks as follows.
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```
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This example was too long and was cropped:
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{
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"abstract": "\" we have studied the leptonic decay @xmath0 , via the decay channel @xmath1 , using a sample of tagged @xmath2 decays collected...",
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"article": "\"the leptonic decays of a charged pseudoscalar meson @xmath7 are processes of the type @xmath8 , where @xmath9 , @xmath10 , or @...",
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"section_names": "[sec:introduction]introduction\n[sec:detector]data and the cleo- detector\n[sec:analysys]analysis method\n[sec:conclusion]summary"
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}
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```
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### Data Fields
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The data fields are the same among all splits.
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#### arxiv
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- `article`: a `string` feature.
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- `abstract`: a `string` feature.
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- `section_names`: a `string` feature.
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- `embeddings`: a `float` 768 dimensional vector
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### Data Splits
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| name |train |validation|test|
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|------|-----:|---------:|---:|
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|arxiv |203037| 6436|6440|
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## Dataset Creation
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### Curation Rationale
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Source Data
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#### Initial Data Collection and Normalization
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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#### Who are the source language producers?
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Annotations
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#### Annotation process
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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#### Who are the annotators?
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Personal and Sensitive Information
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Discussion of Biases
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Other Known Limitations
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Additional Information
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### Dataset Curators
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Licensing Information
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Citation Information
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```
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@article{Cohan_2018,
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title={A Discourse-Aware Attention Model for Abstractive Summarization of
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Long Documents},
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url={http://dx.doi.org/10.18653/v1/n18-2097},
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DOI={10.18653/v1/n18-2097},
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journal={Proceedings of the 2018 Conference of the North American Chapter of
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the Association for Computational Linguistics: Human Language
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Technologies, Volume 2 (Short Papers)},
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publisher={Association for Computational Linguistics},
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author={Cohan, Arman and Dernoncourt, Franck and Kim, Doo Soon and Bui, Trung and Kim, Seokhwan and Chang, Walter and Goharian, Nazli},
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year={2018}
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}
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```
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### Contributions
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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.
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