This research evaluates how large language models like GPT-4 and LLaMA2 can detect misinformation through different approaches - text-only, multimodal, and agent-based methods.

• Text-based approaches analyze content for factual inconsistencies
• Multimodal detection examines both text and visual elements together
• Agentic systems use collaborative AI agents to verify information
• Research identifies which methods are more effective against specific types of digital falsehoods

Security Impact: As misinformation threatens digital ecosystems and societal trust, these evaluated detection mechanisms offer scalable solutions to identify false information before it causes harm.

Original Paper: Unmasking Digital Falsehoods: A Comparative Analysis of LLM-Based Misinformation Detection Strategies