SimpleToM Dataset
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.
Introduction détaillée
The SimpleToM dataset provides a comprehensive set of scenarios to test models' understanding of beliefs and actions. Each scenario includes a context, a question, and multiple choice answers, making it suitable for researchers working on theory of mind and natural language processing. The dataset is available on Hugging Face, ensuring easy access and integration with existing models.
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Hugging Face Dataset - NamelessAI Helply
This paper discusses Helply - a synthesized ML training dataset focused on psychology and therapy, created by Alex Scott and published by NamelessAI. The dataset developed by Alex Scott is a comprehensive collection of synthesized data designed to train LLMs in understanding psychological and therapeutic contexts. This dataset aims to simulate real-world interactions between therapists and patients, enabling ML models to learn from a wide range of scenarios and therapeutic techniques.
Question-Level Feature Extraction on DAIC-WOZ Dataset
The DAIC-WOZ dataset contains clinical interviews designed to support the diagnosis of psychological distress conditions such as anxiety, depression, and post-traumatic stress disorder. This repository provides code for extracting question-level features from the DAIC-WOZ dataset, which can be used for multimodal analysis of depression levels.
American National Mental Health Services Survey
The American National Mental Health Services Survey (N-MHSS) is an annual survey conducted by the Substance Abuse and Mental Health Services Administration (SAMHSA) to collect data on mental health treatment facilities across the United States. The survey provides detailed information on the services and characteristics of these facilities, helping to inform policy and improve mental health care.