Simulating Human-Like Counseling: A Path- and Scenario-Guided Framework for Psychological Support Dialogue

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Authors: Association for Artificial Intelligence 2026, Fang Kong, Maodong Li, Yuanchen Shi, Xiuhong Wang, Longyin Zhang, Yibin Zheng
Cited by: 0

Abstract

The growing demand for psychological support underscores the lack of high-quality counseling dialogue datasets, particularly in non-English contexts. We propose PGSim, a Path-Guided Simulation framework that mirrors real counseling processes—symptom description, problem identification, cause analysis, strategy planning, and iterative adjustment. PGSim models each user scenario as a fine-grained quadruple {Group, Psychological Problem, Problem Cause, Support Focus} and guides dialogue generation through expert-annotated strategy paths. Real counseling dialogues and expert-edited samples are used to fine-tune two language models: a Dialog Generator for strategy-aligned dialogue creation and a Dialog Modifier for expert-level refinement. After automated and human verification, we construct the Chinese Psychological support Dialogue Dataset (CPsDD), containing 68K dialogues across 13 groups, 16 problems, 13 causes, and 12 support focuses. We further present the Comprehensive Agent Dialogue Support System (CADSS), which integrates profiling, summarization, strategy planning, and empathetic response. Experiments on CPsDD and ESConv demonstrate that CADSS achieves state-of-the-art results on Strategy Prediction and Emotional Support Conversation tasks.

Fields of Study & Subjects

Speech and dialogue systems Emotion and Mood Recognition Intelligent Tutoring Systems and Adaptive Learning

Publication details

Journal / source
Underline Science Inc.
Publication date
7 January 2026
Language
EN