  This paper presents and evaluates a new retrieval augmented generation (RAG)
and large language model (LLM)-based artificial intelligence (AI) technique:
rubric enabled generative artificial intelligence (REGAI). REGAI uses rubrics,
which can be created manually or automatically by the system, to enhance the
performance of LLMs for evaluation purposes. REGAI improves on the performance
of both classical LLMs and RAG-based LLM techniques. This paper describes
REGAI, presents data regarding its performance and discusses several possible
application areas for the technology.
