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Updated: Jan 15, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
Computational and ethical considerations for using large language models in psychotherapy
Renwen Zhang1, Han Meng2, Marion Neubronner3
1Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore, Singapore.
Abstract:
Large language models (LLMs) hold great potential for augmenting psychotherapy by enhancing accessibility, personalization and engagement. However, a systematic understanding of the roles that LLMs can play in psychotherapy remains underexplored. In this Perspective, we propose a taxonomy of LLM roles in psychotherapy that delineates six specific roles of LLMs across two key dimensions: artificial intelligence autonomy and emotional engagement. We discuss key computational and ethical challenges, such as emotion recognition, memory retention, privacy and emotional dependency, and offer recommendations to address these challenges.
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