Large language models’ inability to attribute their claims to external knowledge and their tendency to hallucinate makes it difficult to trust their responses. Even humans are prone to factual errors in their writing. Therefore verifying the factual accuracy of textual information, whether generated by large language models or curated by humans, is an important task. However, manually validating and correcting factual errors tends to be a tedious and labor-intensive process. In this paper, we propose FLEEK for automatic fact verification and correction. FLEEK automatically extracts factual…Apple Machine Learning Research