SelfCheckAgent introduces a novel three-agent framework to detect hallucinations in Large Language Models without requiring additional resources.

Key innovations:

• Integrates Symbolic, Specialized Detection, and Contextual Consistency agents for multi-dimensional verification
• Leverages Llama 3.1 capabilities for contextual consistency checking
• Provides robust detection without external knowledge bases
• Creates a more reliable foundation for AI deployment in critical environments

Security implications: By accurately identifying false information generated by AI systems, SelfCheckAgent addresses a critical security challenge for trustworthy LLM deployment, reducing risks associated with AI-generated misinformation in sensitive contexts.

SelfCheckAgent: Zero-Resource Hallucination Detection in Generative Large Language Models