aiqbench analysis
This research proposes a visual control panel interface designed to guide users in formulating effective prompts for Large Language Models, shifting the interaction paradigm from pure recall to recognition-based intent expression. By providing semantic cues within the prompt window, this approach aims to bridge the guidance gap inherent in standard blank text inputs and improve overall user efficiency with AI systems.
Control panels to clarify user intent with Large Language Models
arXiv:2607.21598v1 Announce Type: cross Abstract: Typical user interfaces for Large Language Models present a blank prompt window that invites a natural language query by users, but offers little guidance. This paper proposes a visual control panel interface that would provide more cues to the semantics of prompt formation, enabling users to more easily express their intent. By emphasizing recognition over recall, control panels help users formulate more effective prompts that match their intent.
Abstract:Typical user interfaces for Large Language Models present a blank prompt window that invites a natural language query by users, but offers little guidance. This paper proposes a visual control panel interface that would provide more cues to the semantics of prompt formation, enabling users to more easily express their intent. By emphasizing recognition over recall, control panels help users formulate more effective prompts that match their intent.
Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI)
arXiv:2607.21598 [cs.HC]
(or arXiv:2607.21598v1 [cs.HC] for this version)
https://doi.org/10.48550/arXiv.2607.21598 Focus to learn more arXiv-issued DOI via DataCite
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Full text under the publisher's open licence · 163 words
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