Psychotherapy summarisation poses unique challenges due to the emotional nuance, relational complexity, and non-linear discourse of therapeutic dialogues. Existing large language models (LLMs), even when fine-tuned, often fail to capture these structures, leading to clinically incomplete or incoherent summaries. In thi...
P. K. Adhikary, Ankita Mukherjee, Koushik Sinha Deb et al.· IEEE journal of biomedical a...· 0 citations
Graph2Counsel is introduced, a framework for generating synthetic counseling sessions grounded in Client Psychological Graphs that encode relationships among clients'thoughts, emotions, and behaviors, and Therapy-Eval is introduced, a multi-turn evaluation framework, and the effectiveness of the fine-tuned model in rea...
Aishik Mandal, Hiba Arnaout, Clarissa W. Ong et al.· arXiv.org· 3 citations
The growing demand for scalable psychological counseling highlights the need for high-quality, privacy-compliant data, yet such data remains scarce. Here we introduce MAGneT, a novel multi-agent framework for synthetic psychological counseling session generation that decomposes counselor response generation into coordi...
