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.
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.
The DS4C dataset is a structured collection of COVID-19 data from South Korea, based on reports from the Korea Centers for Disease Control & Prevention (KCDC) and local governments. It includes information on infections, patient routes, and various analyses. The dataset has been used for multiple research and visualization projects.
Collaborative assessment as an intervention in the treatment of mental Illness: a systematic review
The World Health Organization (WHO) provides a comprehensive collection of global health data, including mental health statistics. This resource offers insights into various mental health conditions and their prevalence, helping researchers and policymakers understand and address mental health challenges worldwide.