The Chinese Psychological QA DataSet is a collection of 102,845 community Q&A pairs related to psychological topics., providing a rich source of data for research and development in psychological counseling and AI applications. Each entry includes detailed question and answer information, making it a valuable resource for understanding user queries and generating appropriate responses.
The Chinese Psychological QA DataSet is a comprehensive dataset containing 102,845 community Q&A pairs. Each entry includes detailed information such as the question title, content, answer count, reward number, and question labels. This dataset is designed to support the development of AI-powered psychological counseling tools and chatbots. It includes a wide range of topics and detailed annotations, making it suitable for tasks such as question answering, sentiment analysis, and dialogue generation. The dataset also provides statistical information like the number of comforts given to the questioner, the number of collections, and the number of replies. This dataset is valuable for researchers and developers working on psychological question-answering systems or related applications.
HeartLink is an empathetic psychological model that uses a large language model fine-tuned on a large empathetic Q&A dataset. It can perceive users' emotions and experiences during conversations and provide empathetic responses using rich psychological knowledge, aiming to understand, comfort, and support users. The responses include emoji expressions to bridge the gap with users, offering psychological support and help during consultations.
Psychology Wiki Datasetpsychology_wiki数据集的构建基于心理学领域的英文维基百科内容,通过系统化的数据采集与整理,确保了信息的广泛覆盖与深度挖掘。数据集中的每一篇文章均经过严格的筛选与标注,涵盖了标题、正文、相关性、受欢迎程度及排名等多个维度,为心理学研究提供了丰富的文本资源。
The IC-AnnoMI repository contains source code and a synthetic dataset generated through in-context zero-shot LLM prompting for mental health and therapeutic counselling. IC-AnnoMI is a project that generates contextual MI dialogues using large language models (LLMs). The project contains source code and a synthetic dataset generated through zero-shot prompts, aiming to address the data scarcity and inherent bias problems in mental health and therapeutic consultation.