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Study: Transparency is Often Lacking in Datasets Used to Train Large Language Models
| dc.contributor.author | Zewe, Adam | |
| dc.date.accessioned | 2024-10-31T13:05:02Z | |
| dc.date.available | 2024-10-31T13:05:02Z | |
| dc.date.issued | 2024-08-30 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/157453 | |
| dc.description.abstract | Researchers 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.publisher | MIT News | en_US |
| dc.subject | LLSC | en_US |
| dc.subject | AI | en_US |
| dc.title | Study: Transparency is Often Lacking in Datasets Used to Train Large Language Models | en_US |
| dc.type | Article | en_US |
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Information about the MIT Lincoln Laboratory Supercomputing Center