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- license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ - original
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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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+ - config_name: pubmed
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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: 2252027383
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+ num_examples: 119924
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+ - name: validation
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+ num_bytes: 127403398
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+ num_examples: 6633
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+ - name: test
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+ num_bytes: 127184448
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+ num_examples: 6658
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+ download_size: 4504646347
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+ dataset_size: 2506615229
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  ---
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+
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+ # Dataset Card for "scientific_papers"
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+
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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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+
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+ ## Dataset Description
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+
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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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+ - **Size of downloaded dataset files:** 9.01 GB
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+ - **Size of the generated dataset:** 10.09 GB
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+ - **Total amount of disk used:** 19.10 GB
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+
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+ ### Dataset Summary
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+
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+ Scientific papers datasets contains two sets of long and structured documents.
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+ The datasets are obtained from ArXiv and PubMed OpenAccess repositories.
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+
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+ Both "arxiv" and "pubmed" have two features:
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+ - article: the body of the document, paragraphs separated by "/n".
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+ - abstract: the abstract of the document, paragraphs separated by "/n".
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+ - section_names: titles of sections, separated by "/n".
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+
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+ ### Supported Tasks and Leaderboards
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+
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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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+
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+ ### Languages
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+
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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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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ #### arxiv
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+
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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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+
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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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+ {
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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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+
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+ #### pubmed
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+
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+ - **Size of downloaded dataset files:** 4.50 GB
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+ - **Size of the generated dataset:** 2.51 GB
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+ - **Total amount of disk used:** 7.01 GB
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+
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+ An example of 'validation' 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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+ {
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+ "abstract": "\" background and aim : there is lack of substantial indian data on venous thromboembolism ( vte ) . \\n the aim of this study was...",
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+ "article": "\"approximately , one - third of patients with symptomatic vte manifests pe , whereas two - thirds manifest dvt alone .\\nboth dvt...",
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+ "section_names": "\"Introduction\\nSubjects and Methods\\nResults\\nDemographics and characteristics of venous thromboembolism patients\\nRisk factors ..."
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+ }
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+ ```
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+
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+ ### Data Fields
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+
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+ The data fields are the same among all splits.
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+
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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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+
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+ #### pubmed
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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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+
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+ ### Data Splits
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+
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+ | name |train |validation|test|
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+ |------|-----:|---------:|---:|
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+ |arxiv |203037| 6436|6440|
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+ |pubmed|119924| 6633|6658|
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+
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+ ## Dataset Creation
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+
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+ ### Curation Rationale
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+
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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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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+
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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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+
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+ #### Who are the source language producers?
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+
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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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+
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+ ### Annotations
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+
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+ #### Annotation process
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+
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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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+
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+ #### Who are the annotators?
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+
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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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+
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+ ### Personal and Sensitive Information
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+
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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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+
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+ ## Considerations for Using the Data
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+
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+ ### Social Impact of Dataset
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+
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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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+
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+ ### Discussion of Biases
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+
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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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+
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+ ### Other Known Limitations
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+
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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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+
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+ ## Additional Information
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+
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+ ### Dataset Curators
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+
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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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+
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+ ### Licensing Information
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+
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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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+
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+ ### Citation Information
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+
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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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+
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+ ### Contributions
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+
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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.