Stopping LLM Hallucinations with "Physical Core Constraints": IDE / Nomological Ring Axioms

This article proposes a design principle to prevent Large Language Models (LLMs) from answering when they should not, framing it as a "Fail-Closed" system. It focuses on structural constraints rather than accuracy improvements or benchmark competitions. The core idea revolves around using "Physical Core Constraints" and concepts like IDE (Ideal, Defined, Enforced) and Nomological Ring Axioms to ensure LLMs refrain from generating responses in uncertain or inappropriate situations. This approach aims to enhance the safety and reliability of LLMs by preventing them from hallucinating or providing incorrect information when faced with insufficient data or ambiguous queries. The article emphasizes a proactive, preventative approach to LLM safety.

• •Focus on preventing LLM hallucinations through structural constraints.
• •Utilize "Physical Core Constraints" for enhanced safety.
• •Employ IDE and Nomological Ring Axioms to define acceptable LLM behavior.