@inproceedings{momii-etal-2024-rag,
title = "{RAG}-Fusion Based Information Retrieval for Fact-Checking",
author = "Momii, Yuki and
Takiguchi, Tetsuya and
Ariki, Yasuo",
editor = "Schlichtkrull, Michael and
Chen, Yulong and
Whitehouse, Chenxi and
Deng, Zhenyun and
Akhtar, Mubashara and
Aly, Rami and
Guo, Zhijiang and
Christodoulopoulos, Christos and
Cocarascu, Oana and
Mittal, Arpit and
Thorne, James and
Vlachos, Andreas",
booktitle = "Proceedings of the Seventh Fact Extraction and VERification Workshop (FEVER)",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.fever-1.4",
pages = "47--54",
abstract = "Fact-checking involves searching for relevant evidence and determining whether the given claim contains any misinformation. In this paper, we propose a fact verification system based on RAG-Fusion. We use GPT-4o to generate questions from the claim, which helps improve the accuracy of evidence retrieval.Additionally, we adopt GPT-4o for the final judgment module and refine the prompts to enhance the detection accuracy, particularly when the claim contains misinformation. Experiment showed that our system achieved an AVeriTeC Score of 0.3865 on the AVeriTeC test data, significantly surpassing the baseline score of 0.11.",
}
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%0 Conference Proceedings
%T RAG-Fusion Based Information Retrieval for Fact-Checking
%A Momii, Yuki
%A Takiguchi, Tetsuya
%A Ariki, Yasuo
%Y Schlichtkrull, Michael
%Y Chen, Yulong
%Y Whitehouse, Chenxi
%Y Deng, Zhenyun
%Y Akhtar, Mubashara
%Y Aly, Rami
%Y Guo, Zhijiang
%Y Christodoulopoulos, Christos
%Y Cocarascu, Oana
%Y Mittal, Arpit
%Y Thorne, James
%Y Vlachos, Andreas
%S Proceedings of the Seventh Fact Extraction and VERification Workshop (FEVER)
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F momii-etal-2024-rag
%X Fact-checking involves searching for relevant evidence and determining whether the given claim contains any misinformation. In this paper, we propose a fact verification system based on RAG-Fusion. We use GPT-4o to generate questions from the claim, which helps improve the accuracy of evidence retrieval.Additionally, we adopt GPT-4o for the final judgment module and refine the prompts to enhance the detection accuracy, particularly when the claim contains misinformation. Experiment showed that our system achieved an AVeriTeC Score of 0.3865 on the AVeriTeC test data, significantly surpassing the baseline score of 0.11.
%U https://aclanthology.org/2024.fever-1.4
%P 47-54
Markdown (Informal)
[RAG-Fusion Based Information Retrieval for Fact-Checking](https://aclanthology.org/2024.fever-1.4) (Momii et al., FEVER 2024)
ACL