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    <abstract>Recent trends in LLMs development clearly show growing interest in the use and application of sovereign LLMs. The global debate over sovereign LLMs highlights the need for governments to develop their LLMs, tailored to their unique socio-cultural and historical contexts. However, there remains a shortage of frameworks and datasets to verify two critical questions: (1) how well these models align with users’ socio-cultural backgrounds, and (2) whether they maintain safety and technical robustness without exposing users to potential harms and risks. To address this gap, we construct a new dataset and introduce an analytic framework for extracting and evaluating the socio-cultural elements of sovereign LLMs, alongside assessments of their technical robustness. Our experimental results demonstrate that while sovereign LLMs play a meaningful role in supporting low-resource languages, they do not always meet the popular claim that these models serve their target users well. We also show that pursuing this untested claim may lead to underestimating critical quality attributes such as safety. Our study suggests that advancing sovereign LLMs requires a more extensive evaluation that incorporates a broader range of well-grounded and practical criteria.</abstract>
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%0 Conference Proceedings
%T Assessing Socio-Cultural Alignment and Technical Safety of Sovereign LLMs
%A Chae, Kyubyung
%A Kim, Gihoon
%A Lee, Gyuseong
%A Kim, Taesup
%A Lee, Jaejin
%A Kim, Heejin
%Y Christodoulopoulos, Christos
%Y Chakraborty, Tanmoy
%Y Rose, Carolyn
%Y Peng, Violet
%S Findings of the Association for Computational Linguistics: EMNLP 2025
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-335-7
%F chae-etal-2025-assessing
%X Recent trends in LLMs development clearly show growing interest in the use and application of sovereign LLMs. The global debate over sovereign LLMs highlights the need for governments to develop their LLMs, tailored to their unique socio-cultural and historical contexts. However, there remains a shortage of frameworks and datasets to verify two critical questions: (1) how well these models align with users’ socio-cultural backgrounds, and (2) whether they maintain safety and technical robustness without exposing users to potential harms and risks. To address this gap, we construct a new dataset and introduce an analytic framework for extracting and evaluating the socio-cultural elements of sovereign LLMs, alongside assessments of their technical robustness. Our experimental results demonstrate that while sovereign LLMs play a meaningful role in supporting low-resource languages, they do not always meet the popular claim that these models serve their target users well. We also show that pursuing this untested claim may lead to underestimating critical quality attributes such as safety. Our study suggests that advancing sovereign LLMs requires a more extensive evaluation that incorporates a broader range of well-grounded and practical criteria.
%R 10.18653/v1/2025.findings-emnlp.559
%U https://aclanthology.org/2025.findings-emnlp.559/
%U https://doi.org/10.18653/v1/2025.findings-emnlp.559
%P 10579-10600

Markdown (Informal)

[Assessing Socio-Cultural Alignment and Technical Safety of Sovereign LLMs](https://aclanthology.org/2025.findings-emnlp.559/) (Chae et al., Findings 2025)

• Assessing Socio-Cultural Alignment and Technical Safety of Sovereign LLMs (Chae et al., Findings 2025)

ACL

• Kyubyung Chae, Gihoon Kim, Gyuseong Lee, Taesup Kim, Jaejin Lee, and Heejin Kim. 2025. Assessing Socio-Cultural Alignment and Technical Safety of Sovereign LLMs. In Findings of the Association for Computational Linguistics: EMNLP 2025, pages 10579–10600, Suzhou, China. Association for Computational Linguistics.