Understanding Cultural Alignment in Multilingual LLMs via Natural Debate Statements

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Negru, Vlad-Andrei, Lemnaru, Camelia, Surdeanu, Mihai, Potolea, Rodica
Format: Preprint
Publié: 2026
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866912903041384448
author Negru, Vlad-Andrei
Lemnaru, Camelia
Surdeanu, Mihai
Potolea, Rodica
author_facet Negru, Vlad-Andrei
Lemnaru, Camelia
Surdeanu, Mihai
Potolea, Rodica
contents In this work we investigate the sociocultural values learned by large language models (LLMs). We introduce a novel open-access dataset, Sociocultural Statements, constructed from natural debate statements using a multi-step methodology. The dataset is synthetically labeled to enable the quantization of sociocultural norms and beliefs that LLMs exhibit in their responses to these statements, according to the Hofstede cultural dimensions. We verify the accuracy of synthetic labels using human quality control on a representative sample. We conduct a comparative analysis between two groups of LLMs developed in different countries (U.S. and China), and use as a comparative baseline patterns observed in human measurements. Using this new dataset and the analysis above, we found that culturally-distinct LLMs reflect the values and norms of the countries in which they were developed, highlighting their inability to adapt to the sociocultural backgrounds of their users.
format Preprint
id arxiv_https___arxiv_org_abs_2602_12878
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Understanding Cultural Alignment in Multilingual LLMs via Natural Debate Statements
Negru, Vlad-Andrei
Lemnaru, Camelia
Surdeanu, Mihai
Potolea, Rodica
Computers and Society
In this work we investigate the sociocultural values learned by large language models (LLMs). We introduce a novel open-access dataset, Sociocultural Statements, constructed from natural debate statements using a multi-step methodology. The dataset is synthetically labeled to enable the quantization of sociocultural norms and beliefs that LLMs exhibit in their responses to these statements, according to the Hofstede cultural dimensions. We verify the accuracy of synthetic labels using human quality control on a representative sample. We conduct a comparative analysis between two groups of LLMs developed in different countries (U.S. and China), and use as a comparative baseline patterns observed in human measurements. Using this new dataset and the analysis above, we found that culturally-distinct LLMs reflect the values and norms of the countries in which they were developed, highlighting their inability to adapt to the sociocultural backgrounds of their users.
title Understanding Cultural Alignment in Multilingual LLMs via Natural Debate Statements
topic Computers and Society
url https://arxiv.org/abs/2602.12878