计算机科学
桥(图论)
衔接(社会学)
软件
用户友好型
人机交互
多媒体
万维网
医学
政治
政治学
内科学
法学
程序设计语言
操作系统
标识
DOI:10.1145/3586182.3625121
摘要
Nowadays, novice users often turn to digital tutorials for guidance in software. However, searching and utilizing the tutorial remains a challenge due to the request for proper problem articulation, extensive searches and mind-intensive follow-through. We introduce "Docent", a system designed to bridge this knowledge-seeking gap. Powered by Large Language Models (LLMs), Docent takes vague user input and recent digital operation contexts to reason, seek, and present the most relevant tutorials in-situ. We assume that Docent smooths the user experience and facilitates learning of the software.
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