sources: 28105

This table contains all the sources for our datasets. The description column contains JSON encoded as text that contains useful additional fields like a longer descriptive text "additionalInfo".

This data as json

id name description createdAt updatedAt datasetId additionalInfo link dataPublishedBy
28105 Papers With Code (2023) 
{
    "link": "https://paperswithcode.com/",
    "retrievedDate": "2023-06-14",
    "additionalInfo": "The goal of Papers With Code website is to compile a comprehensive collection of ML papers, code implementations, datasets, methods, and evaluation tables, all made freely available.\n\nThe comparisons to human performance are very approximate and based on small samples of people \u2014 they are only meant to give a rough comparison. You can read more details in the papers that describe the benchmarks:\n\n-Hendrycks et al (2021) Measuring Massive Multitask Language Understanding (MMLU) (page 3): https://arxiv.org/pdf/2009.03300.pdf\n\n-Hendrycks et al (2021) Measuring Mathematical Problem Solving With the MATH Dataset (page 5): https://arxiv.org/pdf/2103.03874v2.pdf\n",
    "dataPublishedBy": "Papers With Code"
}
 2023-07-25 15:52:05 2024-07-08 15:20:30 6102 The goal of Papers With Code website is to compile a comprehensive collection of ML papers, code implementations, datasets, methods, and evaluation tables, all made freely available. The comparisons to human performance are very approximate and based on small samples of people — they are only meant to give a rough comparison. You can read more details in the papers that describe the benchmarks: -Hendrycks et al (2021) Measuring Massive Multitask Language Understanding (MMLU) (page 3): https://arxiv.org/pdf/2009.03300.pdf -Hendrycks et al (2021) Measuring Mathematical Problem Solving With the MATH Dataset (page 5): https://arxiv.org/pdf/2103.03874v2.pdf https://paperswithcode.com/ Papers With Code

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