Taxonomy and Analysis of Sensitive User Queries in Generative AI Search
<|reference_start|>Taxonomy and Analysis of Sensitive User Queries in Generative AI Search: Although there has been a growing interest among industries to integrate generative LLMs into their services, limited experiences and scarcity of resources acts as a barrier in launching and servicing large-scale LLM-based conversational 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.<|reference_end|>
@article{jo2024taxonomy,
    title={Taxonomy and Analysis of Sensitive User Queries in Generative AI Search},
    author={Hwiyeol Jo, Taiwoo Park, Nayoung Choi, Changbong Kim, Ohjoon Kwon,
  Donghyeon Jeon, Hyunwoo Lee, Eui-Hyeon Lee, Kyoungho Shin, Sun Suk Lim,
  Kyungmi Kim, Jihye Lee, Sun Kim},
    journal={arXiv preprint arXiv:2404.08672},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.08672},
    primaryClass={cs.IR cs.AI cs.CL cs.CY cs.LG}
}