PsyProbe: Proactive and Interpretable Dialogue through User State Modeling for Exploratory Counseling

Sohhyung Park, Hyunji Kang, Sungzoon Cho, Dongil Kim


Abstract
Recent advances in large language models have enabled mental health dialogue systems, yet existing approaches remain predominantly reactive, lacking systematic user state modeling for proactive therapeutic exploration. We introduce PsyProbe, a dialogue system designed for the exploration phase of counseling that systematically tracks user psychological states through the PPPPPI framework (Presenting, Predisposing, Precipitating, Perpetuating, Protective, Impact) augmented with cognitive error detection. PsyProbe combines State Builder for extracting structured psychological profiles, Memory Construction for tracking information gaps, Strategy Planner for Motivational Interviewing behavioral codes, and Response Generator with Question Ideation and Critic/Revision modules to generate contextually appropriate, proactive questions. We evaluate PsyProbe with 27 participants in real-world Korean counseling scenarios, including automatic evaluation across ablation modes, user evaluation, and expert evaluation by a certified counselor. The full PsyProbe model consistently outperforms baseline and ablation modes in automatic evaluation. User evaluation demonstrates significantly increased engagement intention and improved naturalness compared to baseline. Expert evaluation shows that PsyProbe substantially improves core issue understanding and achieves question rates comparable to professional counselors, validating the effectiveness of systematic state modeling and proactive questioning for therapeutic exploration.
Anthology ID:
2026.findings-eacl.336
Volume:
Findings of the Association for Computational Linguistics: EACL 2026
Month:
March
Year:
2026
Address:
Rabat, Morocco
Editors:
Vera Demberg, Kentaro Inui, Lluís Marquez
Venue:
Findings
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Publisher:
Association for Computational Linguistics
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Pages:
6390–6411
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https://preview.aclanthology.org/ingest-eacl/2026.findings-eacl.336/
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Cite (ACL):
Sohhyung Park, Hyunji Kang, Sungzoon Cho, and Dongil Kim. 2026. PsyProbe: Proactive and Interpretable Dialogue through User State Modeling for Exploratory Counseling. In Findings of the Association for Computational Linguistics: EACL 2026, pages 6390–6411, Rabat, Morocco. Association for Computational Linguistics.
Cite (Informal):
PsyProbe: Proactive and Interpretable Dialogue through User State Modeling for Exploratory Counseling (Park et al., Findings 2026)
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