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

ArXi:2605.10843v1 Announce Type: cross 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 sociographic disagreement, not consensus, is the primary steering signal. We.