Conversational Topic Recommendation in Counseling and Psychotherapy with Decision Transformer and Large Language Models

Aylin Gunal, Baihan Lin, Djallel Bouneffouf

Abstract
Given the increasing demand for mental health assistance, artificial intelligence (AI), particularly large language models (LLMs), may be valuable for integration into automated clinical support systems. In this work, we leverage a decision transformer architecture for topic recommendation in counseling conversations between patients and mental health professionals. The architecture is utilized for offline reinforcement learning, and we extract states (dialogue turn embeddings), actions (conversation topics), and rewards (scores measuring the alignment between patient and therapist) from previous turns within a conversation to train a decision transformer model. We demonstrate an improvement over baseline reinforcement learning methods, and propose a novel system of utilizing our model’s output as synthetic labels for fine-tuning a large language model for the same task. Although our implementation based on LLaMA-2 7B has mixed results, future work can undoubtedly build on the design.
Anthology ID:
2024.clinicalnlp-1.16
Volume:
Proceedings of the 6th Clinical Natural Language Processing Workshop
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Tristan Naumann, Asma Ben Abacha, Steven Bethard, Kirk Roberts, Danielle Bitterman
Venues:
ClinicalNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
196–201
Language:
URL:
https://aclanthology.org/2024.clinicalnlp-1.16
DOI:
Bibkey:
Cite (ACL):
Aylin Gunal, Baihan Lin, and Djallel Bouneffouf. 2024. Conversational Topic Recommendation in Counseling and Psychotherapy with Decision Transformer and Large Language Models. In Proceedings of the 6th Clinical Natural Language Processing Workshop, pages 196–201, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Conversational Topic Recommendation in Counseling and Psychotherapy with Decision Transformer and Large Language Models (Gunal et al., ClinicalNLP-WS 2024)
Copy Citation:
PDF:
https://preview.aclanthology.org/jeptaln-2024-ingestion/2024.clinicalnlp-1.16.pdf
PDF Search