mlsanityData to 14 Oct 2026

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

arXiv 2601.19096 ↗First posted 27 Jan 2026cs.CLcited by 1

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 7 of its 70 references that are in the map. First posted on arXiv 27 Jan 2026.

Builds on

7 of 70 references.

References · 7

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2020Towards a Human-like Open-Domain Chatbotcited by 470
  3. 2023PLACES: Prompting Language Models for Social Conversation Synthesiscited by 72
  4. 2024The opportunities and risks of large language models in mental healthcited by 54
  5. 2023Knowledge-enhanced Mixed-initiative Dialogue System for Emotional Support Conversationscited by 41
  6. 2023Boosting Distress Support Dialogue Responses with Motivational Interviewing Strategycited by 15
  7. 2018Multi-label Multi-task Deep Learning for Behavioral Codingcited by 12

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.