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papersTODAY 04:00 UTC

Paper Proposes Diagnostics for LLM-Based Synthetic Consumer Panels

A new arXiv preprint examines how large language models are used as stand-ins for survey respondents, a practice that can cut costs dramatically compared with traditional polling. The authors argue that aggregate validation scores hide systematic problems such as compressed variance and flipped coefficient signs, and they offer diagnostic and correction methods to address them.

synthetic-data/llm-evaluation/surveys/benchmarks