Siddhesh Pawar, Arnav Arora, Dustin Wright, Dirk Hovy, Isabelle Augenstein · 2026 · arXiv
DOI: 10.48550/arXiv.2610.31199 · open-access PDF
Large language models (LLMs) serve users whose cultural identities are multi-layered, yet cultural evaluations commonly reduce identity to one label. In this work, we study LLMs under simultaneous identity cues, with a country persona in the system prompt and a second identity signaled in the user turn, either by naming a country (explicit cue) or through the query language (implicit cue). We test World Values Survey (WVS) multiple-choice probing and open-ended sociopolitical generation. In multiple-choice probing, language cues shift answers about three times more than explicit cues but away
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