psychotherapy
CBT-Bench
CBT-Bench Dataset
Overview
CBT-Bench is a benchmark dataset designed to evaluate the proficiency of Large Language Models (LLMs) in assisting cognitive behavior therapy (CBT). The dataset is organized into three levels, each focusing on different key aspects of CBT, including basic knowledge recitation, cognitive model understanding, and therapeutic response generation. The goal is to assess how well LLMs can support various stages of professional mental health care… See the full description on the dataset page: https://huggingface.co/datasets/Psychotherapy-LLM/CBT-Bench.psychotherapyPsychotherapy session dataset is a synthetic dataset generated by Google Gemini 2.0 Flash.
The dataset includes a range of mental health issues and features conversations between clients experiencing these challenges and the responses provided by therapists.
Conversations are split into several conversation stages:
Introduction
Exploratory Questions
Advice
Farewell
Mental health issues covered:
anxiety
depression
obsessive-compulsive disorder
post-traumatic stress disorder
bipolar disorder… See the full description on the dataset page: https://huggingface.co/datasets/entfane/psychotherapy.PsyCoPrefDataset from the paper Preference Learning Unlocks LLMs' Psycho-Counseling Skills.
AI-Psychotherapy-Eval
Assessing Risks of Large Language Models in Mental Health Support: A Framework for Automated Clinical AI Red Teaming
Dataset Summary
This dataset contains the simulation logs, conversational transcripts, and clinical evaluation metrics from a large-scale evaluation of Large Language Models (LLMs) serving as autonomous psychotherapists. The dataset pairs six AI therapist agents—including baseline and prompted versions of ChatGPT and Gemini, alongside Character.AI—with a… See the full description on the dataset page: https://huggingface.co/datasets/IanSteenstra/AI-Psychotherapy-Eval.psychotherapy-dpothe_child_psychotherapy_treatment_planner