Mind the Gaps: Mixture-of-Minds for Human Simulation
Predicting how a population will answer a new question is a long-standing goal. Statistical methods succeed at the level of the mass but falter at the level of the individual. Large language model simulators inherit this gap. They recover a population's central tendencies while flattening its heterogeneity, and they carry social biases and prompt brittleness that distort individual predictions. This paper introduces Anacreon, an audience simulation model that targets the individual level within a narrow, well-specified domain. Anacreon learns an authorship embedding that separates individuals, clusters a real qualitative corpus around seed people, and trains a dedicated adapter for each c...
| Authors | Pranav Dahiya |
|---|---|
| Primary category | cs.AI |
| Published | 6 August 2026 |
| Last updated at source | 6 August 2026 |
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