Claim Verification

Claim verification focuses on automatically assessing the truthfulness of statements, a crucial task given the proliferation of misinformation. Current research heavily utilizes large language models (LLMs), often incorporating techniques like retrieval augmented generation (RAG) and fine-tuning, to analyze claims and supporting evidence retrieved from diverse sources such as PubMed and Wikipedia. This work is driven by the need for robust and explainable systems, leading to the development of benchmarks like CoverBench and new methods that emphasize fact extraction and knowledge-grounded reasoning to improve accuracy and transparency. The ultimate goal is to create reliable automated fact-checking tools to combat misinformation and enhance the trustworthiness of information across various domains.