FIRE: Fact-checking with Iterative Retrieval and Verification (2025.findings-naacl)
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Zhuohan Xie, Rui Xing, Yuxia Wang, Jiahui Geng, Hasan Iqbal, Dhruv Sahnan, Iryna Gurevych, Preslav Nakov
| Challenge: | Fact-checking long-form text is challenging, and breaking it down into multiple atomic claims is not cost-effective. |
| Approach: | They propose a novel agent-based framework that integrates evidence retrieval and claim verification in an iterative manner. |
| Outcome: | The proposed framework reduces large language model (LLM) costs by an average of 7.6 times and search costs by 16.5 times while retaining the same performance. |
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