Using a Large Language Model (LLM) as a judge for evaluating outputs is often done superficially by simply asking for a numerical score. However, a truly effective LLM judge requires a more structured approach, functioning as a 'reasoning contract' rather than just a scoring mechanism. This contract should define the judge's permissible knowledge, the standards guiding its reasoning, the required output format, and the conditions under which its decisions can be overridden. Without these clauses, the numerical scores lack auditability, trustworthiness over time, and accuracy. AI
IMPACT This framework could improve the reliability and auditability of LLM-based evaluation systems.
RANK_REASON The item discusses a conceptual framework for using LLMs as judges, rather than announcing a new product, model, or research finding.
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