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 developin...

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Hauptverfasser: Jo, Hwiyeol, Park, Taiwoo, Choi, Nayoung, Kim, Changbong, Kwon, Ohjoon, Jeon, Donghyeon, Lee, Hyunwoo, Lee, Eui-Hyeon, Shin, Kyoungho, Lim, Sun Suk, Kim, Kyungmi, Lee, Jihye, Kim, Sun
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Sprache:eng
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Zusammenfassung: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.
DOI:10.48550/arxiv.2404.08672