Psy-Insight is a bilingual, interpretable multi-turn dataset for mental health counseling dialogues. It includes 6,208 rounds of multi-turn counseling dialogues in English and 5,776 rounds in Chinese, annotated with step-by-step reasoning labels and multi-task labels. This dataset is designed to support the application of large language models in mental health and is suitable for tasks such as emotion classification and psychological treatment interpretation.
Psy-Insight is a comprehensive dataset designed to support the development of AI applications in mental health counseling. It includes detailed multi-turn dialogues, emotional labels, psychological treatment methods, and step-by-step reasoning annotations. This dataset is ideal for researchers and developers looking to fine-tune large language models for mental health applications.
The SimpleToM dataset is designed to evaluate models' ability to reason about beliefs and actions in various scenarios. It includes a variety of situations with multiple choice questions and answers, covering topics such as food items, personal belongings, and service industries.
SoulChat2.0 is a framework for constructing the digital twin of psychological counselors, designed to support the development of AI applications in mental health. It includes a data generation module and a modeling module, enabling the creation of personalized counseling models based on limited real-world counseling cases.
The ToM QA Dataset is designed to evaluate question-answering models' ability to reason about beliefs. It includes 3 task types and 4 question types, creating 12 total scenarios. The dataset is inspired by theory-of-mind experiments in developmental psychology and is used to test models' understanding of beliefs and inconsistent states of the world.