SoulChat2.0: Psychological Counselor's Digital Twin Framework
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.
Detailed Introduction
SoulChat2.0 is a significant advancement in the field of mental health AI, offering a novel approach to building digital twins of psychological counselors. The framework leverages advanced LLMs to generate high-quality synthetic data that captures the language style and therapeutic techniques of specific counselors. This data is then used to fine-tune models, resulting in AI systems that can provide personalized and effective counseling support.
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Ithaka 2006 Survey of US Higher Education Faculty Attitudes and Behaviors
This study surveys the attitudes and behaviors of US higher education faculty members regarding online resources, the library, and related topics. It covers a wide range of issues, including faculty dependence on electronic scholarly resources, the transition from print to electronic journals, publishing preferences, e-books, and the preservation of scholarly journals.
MentalManip: 心理操纵检测数据集
MentalManip数据集是由Wang等人（2024b）引入的，专门用于检测和分类心理操纵的对话数据集。该数据集包含4000个多轮虚构对话，来源于在线电影剧本，并进行了多层次的标注，包括操纵的存在、操纵技巧和目标脆弱性。数据集的创建旨在通过高质量的标注确保数据的一致性和准确性，从而支持心理操纵检测的研究。
ToM QA Dataset: Evaluating Theory of Mind in Question Answering
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.