Understanding the 4 Main Approaches to LLM Evaluation (From Scratch)

The article outlines four primary methods for evaluating Large Language Models: multiple-choice benchmarks, verifiers, leaderboards, and LLM judges, each with distinct advantages for assessing model performance.

These evaluation approaches range from standardized testing frameworks to using other LLMs as judges, providing different perspectives on model capabilities.

The piece includes code examples to illustrate how each evaluation method works in practice.