Human-Centered LLM-Agent User Interface: A Position Paper

• URL: http://arxiv.org/abs/2405.13050v2
• Date: Mon, 23 Sep 2024 16:41:04 GMT
• Title: Human-Centered LLM-Agent User Interface: A Position Paper
• Authors: Daniel Chin, Yuxuan Wang, Gus Xia,
• Abstract summary: Large Language Model (LLM) -in-the-loop applications have been shown to effectively interpret the human user's commands. A user mostly ignorant to the underlying tools/systems should be able to work with a LAUI to discover an emergent workflow.
• Score: 8.675534401018407
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Large Language Model (LLM) -in-the-loop applications have been shown to effectively interpret the human user's commands, make plans, and operate external tools/systems accordingly. Still, the operation scope of the LLM agent is limited to passively following the user, requiring the user to frame his/her needs with regard to the underlying tools/systems. We note that the potential of an LLM-Agent User Interface (LAUI) is much greater. A user mostly ignorant to the underlying tools/systems should be able to work with a LAUI to discover an emergent workflow. Contrary to the conventional way of designing an explorable GUI to teach the user a predefined set of ways to use the system, in the ideal LAUI, the LLM agent is initialized to be proficient with the system, proactively studies the user and his/her needs, and proposes new interaction schemes to the user. To illustrate LAUI, we present Flute X GPT, a concrete example using an LLM agent, a prompt manager, and a flute-tutoring multi-modal software-hardware system to facilitate the complex, real-time user experience of learning to play the flute.

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