FACT-GPT: Fact-Checking Augmentation Via Claim Matching with LLMs
WWW '24 Companion Proceedings of the ACM on Web Conference 2024(2024)
摘要
Our society is facing rampant misinformation harming public health and trust.To address the societal challenge, we introduce FACT-GPT, a system leveragingLarge Language Models (LLMs) to automate the claim matching stage offact-checking. FACT-GPT, trained on a synthetic dataset, identifies socialmedia content that aligns with, contradicts, or is irrelevant to previouslydebunked claims. Our evaluation shows that our specialized LLMs can match theaccuracy of larger models in identifying related claims, closely mirroringhuman judgment. This research provides an automated solution for efficientclaim matching, demonstrates the potential of LLMs in supporting fact-checkers,and offers valuable resources for further research in the field.
更多查看译文
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要