Universitat Pompeu Fabra
2026-03-06T15:07:29Z
2026-03-06T15:07:29Z
2022
2026-03-06T15:07:29Z
We propose a new task aimed at countering dis- and misinformation, called Finding Reliable Sources. Given a one-sentence claim, the challenge is to automatically find a knowledge source (e.g. a book, a research article, a web page) that could support or refute the claim. We show that this capability could be learnt by observing associations between sentences in English Wikipedia and citations provided for them. Thus, we collect a corpus of over 50 million references to 24 million identified sources with the citation context from Wikipedia, and build search indices using several meaning representation methods. For evaluation, apart from the Wikipedia corpus, we prepare another test set based on the FEVER fact-checking dataset.
This work was supported by thePolish National Agency for AcademicExchangethrough aPolish Returnsgrant number PPN/PPO/2018/1/00006.
Chapter or part of a book
Accepted version
English
Finding reliable sources; Misinformation; Factchecking; Fake news
Institute of Electrical and Electronics Engineers (IEEE)
Proceedings of the 2022 International Joint Conference on Neural Networks (IJCNN); 2022 July 18-23. Padua, Italy. New York: IEEE; 2022.
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. http://dx.doi.org/10.1109/IJCNN55064.2022.9891941
