@inproceedings{jo-etal-2025-taxonomy,
    title = "Taxonomy and Analysis of Sensitive User Queries in Generative {AI} Search System",
    author = "Jo, Hwiyeol  and
      Park, Taiwoo  and
      Lee, Hyunwoo  and
      Choi, Nayoung  and
      Kim, Changbong  and
      Kwon, Ohjoon  and
      Jeon, Donghyeon  and
      Lee, Eui-Hyeon  and
      Shin, Kyoungho  and
      Lim, Sun Suk  and
      Kim, Kyungmi  and
      Lee, Jihye  and
      Kim, Sun",
    editor = "Chiruzzo, Luis  and
      Ritter, Alan  and
      Wang, Lu",
    booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.findings-naacl.195/",
    pages = "3514--3529",
    ISBN = "979-8-89176-195-7",
    abstract = "Although there has been a growing interest among industries in integrating generative LLMs into their services, limited experience and scarcity of resources act as a barrier in launching and servicing large-scale LLM-based services. In this paper, we share our experiences in developing and operating generative AI models within a national-scale search engine, with a specific focus on the sensitiveness of user queries. We propose a taxonomy for sensitive search queries, outline our approaches, and present a comprehensive analysis report on sensitive queries from actual users. We believe that our experiences in launching generative AI search systems can contribute to reducing the barrier in building generative LLM-based services."
}