@inproceedings{minggad-etal-2026-monculture,
    title = "{M}on{C}ulture-Eval: A Hierarchical Benchmark for Evaluating {M}ongolian Cultural Capabilities of Large Language Models across Scripts and Regions",
    author = "Minggad, Quulgan  and
      Zinan, Xiao  and
      Sun, Yuan",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.findings-acl.1449/",
    pages = "28997--29014",
    ISBN = "979-8-89176-395-1",
    abstract = "While Large Language Models (LLMs) have achieved impressive linguistic fluency in low-resource languages, their capacity to process deep cultural nuances remains insufficiently quantified. This paper introduces MonCulture-Eval, a benchmark designed to assess the cultural intelligence of LLMs in the Mongolian context across two writing systems (Traditional and Cyrillic) and three regional sub-cultures (Alxa, Ordos, and Horqin). Curated entirely from primary, non-digitized archives to prevent data contamination, the benchmark employs a three-layer cognitive hierarchy{---}Factual, Situational, and Values{---}supplemented by specialized tasks including Riddles, Taboos, and Proverbs. Evaluation of frontier models reveals a severe ``Script Gap'' and a systematic ``Etic Bias,'' where models sanitize spiritual rituals into secular functional norms."
}