Papers by Minseok Kang

3 papers
Cactus: Towards Psychological Counseling Conversations using Cognitive Behavioral Theory (2024.findings-emnlp)

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Challenge: Existing models that use large language models are not available due to ethical concerns, and data privacy concerns are a concern.
Approach: They propose a multi-turn dialogue dataset that emulates real-life counseling interactions using the goal-oriented approach of Cognitive Behavioral Therapy (CBT).
Outcome: The proposed model outperforms other models in counseling skills, highlighting its effectiveness and potential as a counseling agent.
PRINCIPLES: Synthetic Strategy Memory for Proactive Dialogue Agents (2025.findings-emnlp)

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Challenge: Existing strategies for proactive dialogue face limitations such as limited strategy coverage and preference bias in planning.
Approach: They propose a synthetic strategy memory for proactive dialogue agents based on large language models . PRINCIPLES is derived through offline self-play simulations and serves as reusable knowledge that guides strategy planning during inference.
Outcome: PRINCIPLES is a synthetic strategy memory for proactive dialogue agents.
Can You Share Your Story? Modeling Clients’ Metacognition and Openness for LLM Therapist Evaluation (2025.findings-acl)

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Challenge: Existing evaluation methods for psychological counseling rely on client simulators that clearly disclose internal states to the therapist, making it difficult to determine whether an LLM therapist can uncover unexpressed perspectives.
Approach: They propose a new evaluation framework featuring a controllable and realistic client simulator which dynamically adapts itself based on the ongoing counseling session.
Outcome: The proposed evaluation framework features a realistic and controllable client simulator which dynamically adapts itself based on the ongoing counseling session, offering a more realistic and challenging evaluation environment.

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