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.
مقدمة مفصلة
The ToM QA Dataset, introduced in the EMNLP 2018 paper 'Evaluating Theory of Mind in Question Answering', provides a comprehensive set of scenarios to test question-answering models. The dataset includes first-order and second-order belief questions, as well as memory and reality questions, to ensure models have a correct understanding of the state of the world and others' beliefs. It is available in four versions: easy with noise, easy without noise, hard with noise, and hard without noise.
المزيدمجموعة البيانات
SmartFlowAI/EmoLLM: Psychology LLM、LLM、The Big Model of Mental Health、Finetune、InternLM2、InternLM2.5、Qwen、ChatGLM、Baichuan、DeepSeek、Mixtral、LLama3、GLM4、Qwen2
Psychology LLM、LLM、The Big Model of Mental Health、Finetune、InternLM2、InternLM2.5、Qwen、ChatGLM、Baichuan、DeepSeek、Mixtral、LLama3、GLM4、Qwen2 - SmartFlowAI/EmoLLM
Mental Health Data at WHO
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.
electronic media datasets - Mental Health Datasets
An evolving list of electronic media datasets used to model mental health status. This repository curates a variety of datasets from different sources, including social media platforms, online forums, and academic studies, to support research in mental health modeling and AI applications.