Datasets:
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README.md
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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: scientific_lay_summarisation
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size_categories:
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- 10K<n<100K
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- 1K<n<10K
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source_datasets:
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- original
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tags:
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- scientific papers
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- lay summarization
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- PLOS
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- eLife
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task_categories:
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- summarization
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task_ids: []
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---
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# Dataset Card for "scientific_lay_summarisation"
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### Dataset Summary
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This repository contains the PLOS and eLife datasets, introduced in the EMNLP 2022 paper "[Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature
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](https://arxiv.org/abs/2210.09932)" .
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Each dataset contains full biomedical research articles paired with expert-written lay summaries (i.e., non-technical summaries). PLOS articles are derived from various journals published by [the Public Library of Science (PLOS)](https://plos.org/), whereas eLife articles are derived from the [eLife](https://elifesciences.org/) journal. More details/anlaysis on the content of each dataset are provided in the paper.
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### Supported Tasks and Leaderboards
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Papers with code - [PLOS](https://paperswithcode.com/sota/lay-summarization-on-plos) and [eLife](https://paperswithcode.com/sota/lay-summarization-on-elife).
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### Languages
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English
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## Dataset Structure
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### Data Instances
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[More Information Needed]
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### Data Fields
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[More Information Needed]
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### Data Splits
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[More Information Needed]
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## Dataset Creation
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### Curation Rationale
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[More Information Needed]
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### Source Data
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#### Initial Data Collection and Normalization
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[More Information Needed]
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#### Who are the source language producers?
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[More Information Needed]
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### Annotations
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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[More Information Needed]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Licensing Information
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[More Information Needed]
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### Citation Information
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```
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"Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature"
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Tomas Goldsack, Zhihao Zhang, Chenghua Lin, Carolina Scarton
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EMNLP 2022
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```
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### Contributions
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Thanks to [@TGoldsack1](https://github.com/TGoldsack1) for adding this dataset.
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