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.
상세 소개
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.
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The Lothian Diary Project - Oct 2020
The Lothian Diary Project consists of 125+ audio/video recordings collected from residents of Edinburgh and the Lothian counties in Scotland. Participants discuss their experiences during different stages of the Covid-19 pandemic. The recordings are accompanied by transcriptions and demographic information.
HappyDB: a happiness database of 100,000 happy moments
HappyDB is a crowd-sourced collection of 100,000 happy moments designed to advance the understanding of happiness through text analysis. The database is publicly available and aims to support research in natural language processing (NLP) and positive psychology. It provides insights into the causes of happiness and suggests sustainable actions for improving well-being.
Emotional First Aid Dataset: Psychological Counseling QA Corpus
The Emotional First Aid Dataset is a comprehensive Chinese psychological counseling QA corpus, featuring 20,000 multi-turn dialogues. It is designed to support the development of AI applications in the field of psychological counseling and is available for research purposes.