FZI-WIM at AVeriTeC Shared Task: Real-World Fact-Checking with Question Answering

Jin Liu, Steffen Thoma, Achim Rettinger


Abstract
This paper describes the FZI-WIM system at the AVeriTeC shared Task, which aims to assess evidence-based automated fact-checking systems for real-world claims with evidence retrieved from the web. The FZI-WIM system utilizes open-source models to build a reliable fact-checking pipeline via question-answering. With different experimental setups, we show that more questions lead to higher scores in the shared task. Both in question generation and question-answering stages, sampling can be a way to improve the performance of our system. We further analyze the limitations of current open-source models for real-world claim verification. Our code is publicly available https://github.com/jens5588/FZI-WIM-AVERITEC.
Anthology ID:
2024.fever-1.8
Volume:
Proceedings of the Seventh Fact Extraction and VERification Workshop (FEVER)
Month:
November
Year:
2024
Address:
Miami, Florida, USA
Editors:
Michael Schlichtkrull, Yulong Chen, Chenxi Whitehouse, Zhenyun Deng, Mubashara Akhtar, Rami Aly, Zhijiang Guo, Christos Christodoulopoulos, Oana Cocarascu, Arpit Mittal, James Thorne, Andreas Vlachos
Venue:
FEVER
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
77–85
Language:
URL:
https://aclanthology.org/2024.fever-1.8
DOI:
Bibkey:
Cite (ACL):
Jin Liu, Steffen Thoma, and Achim Rettinger. 2024. FZI-WIM at AVeriTeC Shared Task: Real-World Fact-Checking with Question Answering. In Proceedings of the Seventh Fact Extraction and VERification Workshop (FEVER), pages 77–85, Miami, Florida, USA. Association for Computational Linguistics.
Cite (Informal):
FZI-WIM at AVeriTeC Shared Task: Real-World Fact-Checking with Question Answering (Liu et al., FEVER 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.fever-1.8.pdf