Do LLMs Know Your Neighborhood? Auditing LLM Priors for Neighborhood-Level Mobility Prediction and Structural Alignment
Directional analysis shows that LLMs often rely on coarse, stable predictor-level priors that remain similar across outcomes and cities, including asymmetric treatment of protected-group predictors, and can partially recover aggregate mobility patterns from urban context.
S. Abrar, Eesha Kurella, Arnav Dadarya et al.
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