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                "## Table of Contents\n- [Table of Contents](#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) -",
                "- [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions)\n\n## Dataset Description\n- **Repository**: https:\/\/github.com\/hendrycks\/test - **Paper**: https:\/\/arxiv.org\/abs\/2009.03300\n\n### Dataset Summary\n[Measuring Massive Multitask Language Understanding](https:\/\/arxiv.org\/pdf\/2009.03300) by [Dan Hendrycks](https:\/\/people.eecs.berkeley.edu\/~hendrycks\/), [Collin Burns](http:\/\/collinpburns.com), [Steven Basart](https:\/\/stevenbas.art), Andy Zou, Mantas Mazeika, [Dawn Song](https:\/\/people.eecs.berkeley.edu\/~dawnsong\/), and [Jacob Steinhardt](https:\/\/www.stat.berkeley.edu\/~jsteinhardt\/) (ICLR 2021).",
                "art), Andy Zou, Mantas Mazeika, [Dawn Song](https:\/\/people.eecs.berkeley.edu\/~dawnsong\/), and [Jacob Steinhardt](https:\/\/www.stat.berkeley.edu\/~jsteinhardt\/) (ICLR 2021). This is a massive multitask test consisting of multiple-choice questions from various branches of knowledge. The test spans subjects in the humanities, social sciences, hard sciences, and other areas that are important for some people to learn. This covers 57 tasks including elementary mathematics, US history, computer science, law, and more. To attain high accuracy on this test, models must possess extensive world knowledge and problem solving ability. A complete list of tasks: ['abstract_algebra', 'anatomy', 'astronomy', 'business_ethics', 'clinical_knowledge', 'college_biology', 'college_chemistry', 'college_computer_science', 'college_mathematics', 'college_medicine', 'college_physics', 'computer_security', 'conceptual_physics', 'econometrics', 'electrical_engineering', 'elementary_mathematics', 'formal_logic', 'global_facts', 'high_school_biology',"
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