Automated Fact Checking

Automated fact-checking aims to use computational methods to verify the accuracy of claims, combating the spread of misinformation online. Current research focuses on leveraging large language models (LLMs), often enhanced with knowledge graphs or external evidence retrieval, to assess claim veracity, employing techniques like zero-shot learning and fine-tuning for specific domains. These advancements are crucial for improving the efficiency and scalability of fact-checking, with implications for mitigating the impact of false information across various online platforms and enhancing the reliability of information ecosystems.