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Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors
March 18, 2024, 4:47 a.m. | Guanghua Li, Wensheng Lu, Wei Zhang, Defu Lian, Kezhong Lu, Rui Mao, Kai Shu, Hao Liao
cs.CL updates on arXiv.org arxiv.org
Abstract: The proliferation of fake news has had far-reaching implications on politics, the economy, and society at large. While Fake news detection methods have been employed to mitigate this issue, they primarily depend on two essential elements: the quality and relevance of the evidence, and the effectiveness of the verdict prediction mechanism. Traditional methods, which often source information from static repositories like Wikipedia, are limited by outdated or incomplete data, particularly for emerging or rare claims. …
abstract arxiv cs.ai cs.cl detection detection methods economy fake fake news issue language language models large language large language models politics quality retrieval retrieval-augmented search society truth type
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