Training-Free Cultural Alignment of Large Language Models via Persona Disagreement

Large language models increasingly mediate decisions that turn on moral judgement, yet a growing body of evidence shows that their implicit preferences are not culturally neutral. Existing cultural alignment methods either require per-country preference data and fine-tuning budgets or assume white-box access to model internals that commercial APIs do not expose. In this work, we focus on this realistic black-box, public-data-only regime and observe that within-country sociodemographic disagreeme

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ethics.ai (11 May 2026), “Training-Free Cultural Alignment of Large Language Models via Persona Disagreement,” evidence record 4540, https://ethics.ai/record/4540 (originally published by arXiv).

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