Weiwei Zheng’s research while affiliated with Wuhan University and other places

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Publications (2)


Technical framework for integrating LLMs as assistive tools in philosophical counseling (PC).
Architectural blueprint of an LLM-enabled philosophical counseling recommendation system.
Example of an LLM-generated session summary derived from counseling dialogues.
Process for constructing digital counselor avatars using LLMs-related techniques.
Leveraging RAG for cultural adaptation in counseling contexts.
Leveraging large language models to assist philosophical counseling: prospective techniques, value, and challenges
  • Article
  • Full-text available

March 2025

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43 Reads

Humanities and Social Sciences Communications

Bokai Chen

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Weiwei Zheng

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Liang Zhao

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Xiaojun Ding

Large language models (LLMs) have emerged as transformative tools with the potential to revolutionize philosophical counseling. By harnessing their advanced natural language processing and reasoning capabilities, LLMs offer innovative solutions to overcome limitations inherent in traditional counseling approaches—such as counselor scarcity, difficulties in identifying mental health issues, subjective outcome assessment, and cultural adaptation challenges. In this study, we explore cutting‐edge technical strategies—including prompt engineering, fine‐tuning, and retrieval‐augmented generation—to integrate LLMs into the counseling process. Our analysis demonstrates that LLM-assisted systems can provide counselor recommendations, streamline session evaluations, broaden service accessibility, and improve cultural adaptation. We also critically examine challenges related to user trust, data privacy, and the inherent inability of current AI systems to genuinely understand or empathize. Overall, this work presents both theoretical insights and practical guidelines for the responsible development and deployment of AI-assisted philosophical counseling practices.

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