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Evidence record 5866 · automatically gathered

Can Persona-Prompted LLMs Emulate Subgroup Values? An Empirical Analysis of Generalisability and Fairness in Cultural Alignment

Despite their global prevalence, many Large Language Models (LLMs) are aligned to a monolithic, often Western-centric set of values. This paper investigates the more challenging task of fine-grained value alignment: examining whether LLMs can emulate the distinct cultural values of demographic subgroups. Using Singapore as a case study and the World Values Survey (WVS), we examine the value landscape and show that even state-of-the-art models like GPT-4.1 achieve only 57.4% accuracy in predictin

Record details

Published: 14 April 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Safety & alignment · Finance, VC & PE
Retrieved: 14 July 2026

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How to cite this record

ethics.ai (14 April 2026), “Can Persona-Prompted LLMs Emulate Subgroup Values? An Empirical Analysis of Generalisability and Fairness in Cultural Alignment,” evidence record 5866, https://ethics.ai/record/5866 (originally published by arXiv).

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