Datasets:
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# A cleaned dataset from [paperswithcode.com](https://paperswithcode.com/)
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*Last dataset update: July 2023*
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This is a cleaned up dataset optained from [paperswithcode.com](https://paperswithcode.com/) through their [API](https://paperswithcode.com/api/v1/docs/) service.
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It contains the following tables:
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- tasks.csv
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- areas.csv
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# A cleaned dataset from [paperswithcode.com](https://paperswithcode.com/)
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*Last dataset update: July 2023*
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This is a cleaned up dataset optained from [paperswithcode.com](https://paperswithcode.com/) through their [API](https://paperswithcode.com/api/v1/docs/) service. It represents a set of around 56K carefully categorized papers into 3K tasks and 16 areas. The papers contain arXiv and NIPS IDs as well as title, abstract and other meta information.
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It can be used for training text classifiers that concentrate on the use of specific AI and ML methods and frameworks.
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### Contents
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It contains the following tables:
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- papers.csv (around 56K)
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- papers_train.csv (80% from 56K)
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- papers_test.csv (20% from 56K)
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- tasks.csv
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- areas.csv
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