WikiWhy
WikiWhy: Answering and Explaining Cause-and-Effect Questions
This paper was accepted as a Top 5% paper with Oral Presentation to the International Conference on Learning Representations (ICLR 2023) in Kigali, Rwanda.
WikiWhy is a QA dataset built around a novel auxiliary task: explaining why an answer is true in natural language. WikiWhy contains over 9,000 “why” question-answer-rationale triples, grounded on Wikipedia facts across a diverse set of topics. Each rationale is a set of supporting statements connecting the question to the answer.
Updates
02/24/2023 Added dataset version 1.0
Citation
@inproceedings{
ho2023wikiwhy,
title={WikiWhy: Answering and Explaining Cause-and-Effect Questions},
author={Matthew Ho and Aditya Sharma and Justin Chang and Michael Saxon and Sharon Levy and Yujie Lu and William Yang Wang},
booktitle={International Conference on Learning Representations},
year={2023},
url={https://openreview.net/forum?id=vaxnu-Utr4l}
}