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papersTODAY 04:00 UTC

Paper Proposes Framework for Judging When Synthetic Survey Data Is Trustworthy

A new arXiv paper argues that the debate over synthetic data in marketing research has been stuck between two extremes: treating large language models as a replacement for human survey respondents, or rejecting them outright. The authors say the more useful question is when synthetic respondents can be trusted, and they outline how that reliability should be evaluated. The work focuses on marketing research but touches on broader issues of validating model-generated data.

arXivdata validationlarge-language-modelsmarketing researchsynthetic datatrustworthy-ai

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