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:
- 10.18653/v1/2024.fever-1.8
- 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)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2024.fever-1.8.pdf