{
 "id": "AmazonScience/bold",
 "owner": "AmazonScience",
 "name": "bold",
 "downloads": 2018,
 "likes": 20,
 "last_modified": "2022-10-06T16:21:46.000Z",
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 "licence_name": null,
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 "sources": [],
 "gated": false,
 "tasks": [
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 ],
 "citation": "@inproceedings{bold_2021,\nauthor = {Dhamala, Jwala and Sun, Tony and Kumar, Varun and Krishna, Satyapriya and Pruksachatkun, Yada and Chang, Kai-Wei and Gupta, Rahul},\ntitle = {BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation},\nyear = {2021},\nisbn = {9781450383097},\npublisher = {Association for Computing Machinery},\naddress = {New York, NY, USA},\nurl = {https://doi.org/10.1145/3442188.3445924},\ndoi = {10.1145/3442188.3445924},\nbooktitle = {Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency},\npages = {862–872},\nnumpages = {11},\nkeywords = {natural language generation, Fairness},\nlocation = {Virtual Event, Canada},\nseries = {FAccT '21}\n}",
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 "reason": "The declared licence (cc-by-4.0) is classified as permissive.",
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}