Real World Claim

Real-world claim verification focuses on automatically assessing the truthfulness of factual assertions found in diverse sources like social media and news articles, a crucial task given the proliferation of misinformation. Current research emphasizes developing robust methods for evaluating numerical claims, handling the complexities of real-world evidence, and improving the explainability and reliability of automated fact-checking systems, often employing large language models (LLMs) and deep learning architectures like transformers and convolutional neural networks. This field is vital for combating misinformation, enhancing the trustworthiness of online information, and supporting evidence-based decision-making across various domains.