From National Curricula to Cultural Awareness: Constructing Open-Ended Culture-Specific Question Answering Dataset
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866911360366936064 |
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| author | Yoo, Haneul Cho, Won Ik Kim, Geunhye Han, Jiyoon |
| author_facet | Yoo, Haneul Cho, Won Ik Kim, Geunhye Han, Jiyoon |
| contents | Large language models (LLMs) achieve strong performance on many tasks, but their progress remains uneven across languages and cultures, often reflecting values latent in English-centric training data. To enable practical cultural alignment, we propose a scalable approach that leverages national social studies curricula as a foundation for culture-aware supervision. We introduce CuCu, an automated multi-agent LLM framework that transforms national textbook curricula into open-ended, culture-specific question-answer pairs. Applying CuCu to the Korean national social studies curriculum, we construct KCaQA, comprising 34.1k open-ended QA pairs. Our quantitative and qualitative analyses suggest that KCaQA covers culture-specific topics and produces responses grounded in local sociocultural contexts. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_04632 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | From National Curricula to Cultural Awareness: Constructing Open-Ended Culture-Specific Question Answering Dataset Yoo, Haneul Cho, Won Ik Kim, Geunhye Han, Jiyoon Computation and Language Artificial Intelligence Large language models (LLMs) achieve strong performance on many tasks, but their progress remains uneven across languages and cultures, often reflecting values latent in English-centric training data. To enable practical cultural alignment, we propose a scalable approach that leverages national social studies curricula as a foundation for culture-aware supervision. We introduce CuCu, an automated multi-agent LLM framework that transforms national textbook curricula into open-ended, culture-specific question-answer pairs. Applying CuCu to the Korean national social studies curriculum, we construct KCaQA, comprising 34.1k open-ended QA pairs. Our quantitative and qualitative analyses suggest that KCaQA covers culture-specific topics and produces responses grounded in local sociocultural contexts. |
| title | From National Curricula to Cultural Awareness: Constructing Open-Ended Culture-Specific Question Answering Dataset |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2601.04632 |