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arXiv · 2505.21548

Fluent but Foreign: Even Regional LLMs Lack Cultural Alignment

Dhruv Agarwal·Anya Shukla·Sunayana Sitaram·Aditya Vashistha
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Abstract

Large language models (LLMs) are used worldwide, yet exhibit Western cultural tendencies. Many countries are now building ``regional'' or ``sovereign'' LLMs, but it remains unclear whether they reflect local values and practices or merely speak local languages. Using India as a case study, we evaluate six Indic and six global LLMs on two dimensions -- values and practices -- grounded in nationally representative surveys and community-sourced QA datasets. Across tasks, Indic models do not align better with Indian norms than global models; in fact, a U.S. respondent is a closer proxy for Indian values than any Indic model. We further run a user study with 115 Indian users and find that writing suggestions from both global and Indic LLMs introduce Westernized or exoticized writing. Prompting and regional fine-tuning fail to recover alignment and can even degrade existing knowledge. We attribute this to scarce culturally grounded data, especially for pretraining. We position cultural evaluation as a first-class requirement alongside multilingual benchmarks and offer a reusable, community-grounded methodology. We call for native, community-authored corpora and thickxwide evaluations to build truly sovereign LLMs.

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Dhruv Agarwal, Anya Shukla, Sunayana Sitaram, Aditya Vashistha. 2026-01-22. Fluent but Foreign: Even Regional LLMs Lack Cultural Alignment. https://arxiv.org/abs/2505.21548

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