PALMs: Using Multi Construct-Grounded Rationales for Modeling Population Preferences in LLMs

• URL: http://arxiv.org/abs/2608.01458v1
• Date: Sun, 02 Aug 2026 19:31:59 GMT
• Title: PALMs: Using Multi Construct-Grounded Rationales for Modeling Population Preferences in LLMs
• Abstract summary: We introduce Population Aligned Language Models (PALMs), a suite of models each aligned to specific populations.<n>PALMs are Evaluated across four dimensions: personality, values and beliefs, cultural norms, and morality.<n>We demonstrate strong generalization to downstream applications with- out task-specific supervision.
• Score: 10.940747084451559
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large language models are being extensively used to simulate individual user behavior, yet faithfully representing a population requires capturing the systematic variation in values, beliefs, and cultural norms that distinguish one group from another. We introduce Population Aligned Language Models (PALMs), a suite of models each aligned to specific populations, covering five countries: USA, India, Brazil, France and Italy. PALMs are created by synthesizing rationales grounded in psychological and cultural constructs and using these as latent supervision during preference tuning for population-specific alignment. Evaluated across four dimensions: personality, values and beliefs, cultural norms, and morality, PALMs consistently outperform baselines, including culture-specialized models, achieving an average of 8.59% relative improvement over the best baseline across all five populations. Notably, construct-grounded rationales outperform both demographic prompting and survey-based fine-tuning, suggesting that grounding preference learning in psychology and culture provides a richer inductive signal than surface-level response distributions. We further demonstrate strong generalization to downstream applications with- out task-specific supervision: outperforming best baselines by 5.19% in personalized reward modeling, 6.34% in population simulation, and showing strong transfer to social reasoning tasks. Datasets and code are available at: https://github.com/limenlp/PALMs.

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