NAACL 2025long0 citations

PerCul: A Story-Driven Cultural Evaluation of LLMs in Persian

Erfan Moosavi Monazzah, Vahid Rahimzadeh, Yadollah Yaghoobzadeh, Azadeh Shakery, Mohammad Taher Pilehvar

Abstract

Large language models predominantly reflect Western cultures, largely due to the dominance of English-centric training data. This imbalance presents a significant challenge, as LLMs are increasingly used across diverse contexts without adequate evaluation of their cultural competence in non-English languages, including Persian. To address this gap, we introduce PerCul, a carefully constructed dataset designed to assess the sensitivity of LLMs toward Persian culture. PerCul features story-based, multiple-choice questions that capture culturally nuanced scenarios.Unlike existing benchmarks, PerCul is curated with input from native Persian annotators to ensure authenticity and to prevent the use of translation as a shortcut. We evaluate several state-of-the-art multilingual and Persian-specific LLMs, establishing a foundation for future research in cross-cultural NLP evaluation. Our experiments demonstrate a 11.3% gap between best closed source model and layperson baseline while the gap increases to 21.3% by using the best open-weight model. You can access the dataset from here:https://huggingface.co/datasets/teias-ai/percul

BibTeX
@inproceedings{moosavi-monazzah-etal-2025-percul,
    title = "{P}er{C}ul: A Story-Driven Cultural Evaluation of {LLM}s in {P}ersian",
    author = "Moosavi Monazzah, Erfan  and
      Rahimzadeh, Vahid  and
      Yaghoobzadeh, Yadollah  and
      Shakery, Azadeh  and
      Pilehvar, Mohammad Taher",
    editor = "Chiruzzo, Luis  and
      Ritter, Alan  and
      Wang, Lu",
    booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.naacl-long.631/",
    pages = "12670--12687",
    ISBN = "979-8-89176-189-6"
}
PerCul: A Story-Driven Cultural Evaluation of LLMs in Persian · NAACL 2025