CAAFC 解决了现有自动事实核查系统与专业实践脱节的痛点，做内容审核、AI 安全或信息验证的团队可以直接参考其框架设计，提升事实核查的可靠性和可操作性。
CAAFC 是一个新型自动事实核查框架，旨在解决现有 AFC 系统与专业事实核查实践之间的脱节问题。它不仅能检测事实错误和幻觉，还能通过主要信息源提供可操作的纠正理由。该框架支持对声明、对话和对话内容进行核查，并在必要时更新证据和知识库以纳入最新信息。在多个基准数据集上，CAAFC 超越了当前最先进的 AFC 和幻觉检测系统。这项工作对于应对海量 AI 生成内容中的虚假信息具有重要意义。
CAAFC: Chronological Actionable Automated Fact-Checker for misinformation / non-factual hallucination detection and correction
With the vast amount of content uploaded every hour, along with the AI generated content that can include hallucinations, Automated Fact-Checking (AFC) has become increasingly vital, as it is infeasible for human fact-checkers to manually verify the sheer volume of information generated online. Professional fact-checkers have identified several gaps in existing AFC systems, noting a misalignment between how these systems operate and how fact-checking is performed in practice. In this paper, we introduce CAAFC (Chronological Actionable Automated Fact-Checker), a frame-work designed to bridge these gaps. It surpasses SOTA AFC and hallucination detection systems across multiple benchmark datasets. CAAFC operates on claims, conversations, and dialogues, enabling it not only to detect factual errors and hallucinations, but also to correct them by providing actionable justifications supported by primary information sources. Furthermore, CAAFC can update evidence and knowledge bases by incorporating recent and contextual information when necessary, thereby enhancing the reliability of fact verification.