Evaluating large language models (LLMs) and retrieval-augmented generation (RAG) systems is a complex and nuanced process, reflecting the sophisticated and…
Evaluating large language models (LLMs) and retrieval-augmented generation (RAG) systems is a complex and nuanced process, reflecting the sophisticated and multifaceted nature of these systems. Unlike traditional machine learning (ML) models, LLMs generate a wide range of diverse and often unpredictable outputs, making standard evaluation metrics insufficient. Key challenges include the…