LLM Response Evaluation with Spring AI: Building LLM-as-a-Judge Using Recursive Advisors
The challenge of evaluating Large Language Model (LLM) outputs is critical for notoriously non-deterministic AI applications, especially as they move into production.
Traditional metrics like ROUGE and BLEU fall short when assessing the nuanced, contextual responses that modern LLMs produce. Human evaluation, while accurate, is expensive, slow, and doesn't scale.
Enter LLM-as-a-Judge - a powerful technique that uses LLMs themselves to evaluate the quality of AI-generated content. Research shows that sophisticated judge models can align with human judgment up to 85%, which is actually higher…