COCOA: CBT-based Conversational Counseling Agent using Memory
  Specialized in Cognitive Distortions and Dynamic Prompt
Suyeon Lee Jieun Kang Harim Kim Kyoung-Mee Chung Dongha Lee Jinyoung Yeo
The demand for conversational agents that provide mental health care is
consistently increasing. In this work, we develop a psychological counseling
agent, referred to as CoCoA, that applies Cognitive Behavioral Therapy (CBT)
techniques to identify and address cognitive distortions inherent in the
client's statements. Specifically, we construct a memory system to efficiently
manage information necessary for counseling while extracting high-level
insights about the client from their utterances. Additionally, to ensure that
the counseling agent generates appropriate responses, we introduce dynamic
prompting to flexibly apply CBT techniques and facilitate the appropriate
retrieval of information. We conducted dialogues between CoCoA and characters
from Character.ai, creating a dataset for evaluation. Then, we asked GPT to
evaluate the constructed counseling dataset, and our model demonstrated a
statistically significant difference from other models.