ExPerT infers query-specific user expertise from semantic text and keystroke dynamics via LLM prompting to adapt response generation, cutting inference error 65.7% and raising satisfaction 17.52% in a 40-participant study.
Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems , articleno =
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Qualitative study of 19 CS students using multi-view visualizations reveals selective engagement driven by agency, fit, and legitimacy rather than cognitive load reduction alone.
Hiding generative AI use to signal expertise reduces knowledge sharing and transparency among workplace colleagues.
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ExPerT: Personalizing LLM Responses to Users' Domain Expertise via Query-Wise Semantic and Keystroke Behavioral Cues
ExPerT infers query-specific user expertise from semantic text and keystroke dynamics via LLM prompting to adapt response generation, cutting inference error 65.7% and raising satisfaction 17.52% in a 40-participant study.
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Code as Anchor, Memory and Metaphor as Support: Learner Experiences with Multi-View Visualizations
Qualitative study of 19 CS students using multi-view visualizations reveals selective engagement driven by agency, fit, and legitimacy rather than cognitive load reduction alone.
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"If You're Very Clever, No One Knows You've Used It": The Social Dynamics of Developing Generative AI Literacy in the Workplace
Hiding generative AI use to signal expertise reduces knowledge sharing and transparency among workplace colleagues.