REALM: A Dataset of Real-World LLM Use Cases

Jingwen Cheng, Kshitish Ghate, Wenyue Hua, William Yang Wang, Hong Shen +1 more
3/24/2025
cs.HCcs.AIcs.CL

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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.

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Cite this paper

@article{cheng2025realm,
  title  = {REALM: A Dataset of Real-World LLM Use Cases},
  author = {Jingwen Cheng and Kshitish Ghate and Wenyue Hua and William Yang Wang and Hong Shen and Fei Fang},
  year   = {2025},
  eprint = {2503.18792},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.18792v2}
}

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