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Taxonomy and Analysis of Sensitive User Queries in Generative AI Search
April 16, 2024, 4:42 a.m. | Hwiyeol Jo, Taiwoo Park, Nayoung Choi, Changbong Kim, Ohjoon Kwon, Donghyeon Jeon, Hyunwoo Lee, Eui-Hyeon Lee, Kyoungho Shin, Sun Suk Lim, Kyungmi Kim
cs.LG updates on arXiv.org arxiv.org
Abstract: 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 …
abstract ai search analysis and analysis arxiv conversational cs.ai cs.cl cs.cy cs.ir cs.lg generative generative ai search industries llm llms paper queries resources scale search services taxonomy type
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