@inproceedings{cheng-etal-2025-realm,
    title = "{REALM}: A Dataset of Real-World {LLM} Use Cases",
    author = "Cheng, Jingwen  and
      Ghate, Kshitish  and
      Hua, Wenyue  and
      Wang, William Yang  and
      Shen, Hong  and
      Fang, Fei",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.findings-acl.437/",
    pages = "8331--8341",
    ISBN = "979-8-89176-256-5",
    abstract = "Large Language Models (LLMs), such as the GPT series, have driven significant industrial applications, leading to economic and societal transformations. However, a comprehensive understanding of their real-world applications remains limited.To address this, we introduce **REALM**, a dataset of over 94,000 LLM use cases collected from Reddit and news articles. **REALM** captures two key dimensions: the diverse applications of LLMs and the demographics of their users. It categorizes LLM applications and explores how users' occupations relate to the types of applications they use.By integrating real-world data, **REALM** offers insights into LLM adoption across different domains, providing a foundation for future research on their evolving societal roles. An interactive dashboard ([https://realm-e7682.web.app/](https://realm-e7682.web.app/)) is provided for easy exploration of the dataset."
}