@inproceedings{keleg-2025-llm,
    title = "{LLM} Alignment for the {A}rabs: A Homogenous Culture or Diverse Ones",
    author = "Keleg, Amr",
    editor = "Prabhakaran, Vinodkumar  and
      Dev, Sunipa  and
      Benotti, Luciana  and
      Hershcovich, Daniel  and
      Cao, Yong  and
      Zhou, Li  and
      Cabello, Laura  and
      Adebara, Ife",
    booktitle = "Proceedings of the 3rd Workshop on Cross-Cultural Considerations in NLP (C3NLP 2025)",
    month = may,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.c3nlp-1.1/",
    pages = "1--9",
    ISBN = "979-8-89176-237-4",
    abstract = "Large Language Models (LLMs) have the potential of being a useful tool that can automate tasks, and assist humans. However, these models are more fluent in English and more aligned with Western cultures, norms, and values. Arabic-specific LLMs are being developed to better capture the nuances of the Arabic language, and the views of the Arabs. However, Arabs are sometimes assumed to share the same culture. In this position paper, we discuss the limitations of this assumption and provide our recommendations for how to curate better alignment data that models the cultural diversity within the Arab world."
}