Clarify User Expertise: Towards Proactive Conversational Agents Tailoring Responses to User Proficiency
In the context of information seeking, conversational agents are undergoing an evolution from reactive tools to proactive, personalized assistants. A critical aspect of this evolution is the ability to tailor strategic interactions to a user's unique needs and expectations. Unlike existing studies that focus on proactively clarifying query ambiguities, we center on clarifying the user's expertise in order to tailor responses for better user comprehension. We find that existing agents struggle to determine user expertise from queries alone, a limitation that prevents them from dynamically adapting their responses. To address this gap, we introduce PASSING to empower the agent to proactivel...
| Authors | Zhihong Cao, Chen Huang |
|---|---|
| Primary category | cs.AI |
| Published | 23 August 2026 |
| Last updated at source | 26 August 2026 |
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