PsyAdvisor: A Plug-and-Play Strategy Advice Planner with Proactive Questioning in Psychological Conversations
Yuxin Hu, Danni Liu, Bo Liu, Yida Chen, Jiuxin Cao, Yan Liu
Abstract
Proactive questioning is essential in psychological conversations as it helps uncover deeper issues and unspoken concerns. Current psychological LLMs are constrained by passive response mechanisms, limiting their capacity to deploy proactive strategies for psychological counseling. To bridge this gap, we first develop the ProPsyC (Proactive Psychological Conversation) dataset, a multi-turn conversation dataset with interpretive labels including strategy decision logic and reaction attribution. Based on ProPsyC, we propose PsyAdvisor by supervised fine-tuning, a plug-and-play proactive questioning strategy planner that empowers psychological LLMs to initiate welltimed questioning through strategic prompting. Experimental results demonstrate that psychological LLMs integrated with PsyAdvisor substantially improve proactive questioning capacity, conversation depth, and response quality. Furthermore, PsyAdvisor shows promising potential in assisting novice counselors by providing strategy recommendations. This study provides new optimization directions for psychological conversation systems and offers valuable insights for future research on proactive questioning mechanisms in psychological LLMs. Our code are available at https: //github.com/EthanHu777/PsyAdvisor .
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