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dc.contributor.authorZewe, Adam
dc.date.accessioned2024-10-31T13:05:02Z
dc.date.available2024-10-31T13:05:02Z
dc.date.issued2024-08-30
dc.identifier.urihttps://hdl.handle.net/1721.1/157453
dc.description.abstractResearchers developed an easy-to-use tool that enables an AI practitioner to find data that suits the purpose of their model, which could improve accuracy and reduce bias.en_US
dc.publisherMIT Newsen_US
dc.subjectLLSCen_US
dc.subjectAIen_US
dc.titleStudy: Transparency is Often Lacking in Datasets Used to Train Large Language Modelsen_US
dc.typeArticleen_US


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    Information about the MIT Lincoln Laboratory Supercomputing Center

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