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.
Подробное введение
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.
БольшеНабор данных
ISSP: International Social Science Survey Program
The ISSP is a cross-national collaboration program conducting annual surveys on diverse topics relevant to social sciences. It includes members from various cultures around the globe and provides free access to collected data and documentation.
Cam-CAN Data Access Portal | Cambridge Centre for Ageing and Neuroscience (Cam-CAN) | University of Cambridge
The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) uses epidemiological, behavioral, and neuroimaging data to understand how individuals can best retain cognitive abilities into old age. The Cam-CAN Data Access Portal provides access to datasets from the Cambridge Centre for Ageing and Neuroscience, including neuroimaging and cognitive data from participants aged 18-90.
IC-AnnoMI: In-Context MI Dialogues - GitHub Repository
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.