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

Large language model evaluation involves benchmark-based and judgment-based approaches. Multiple-choice methods like MMLU test knowledge recall through predefined answers, while verifier-based approaches check free-form responses against correct answers using external tools for domains like math and coding. Preference-based leaderboards like LM Arena rank models through user voting, using Elo ratings for dynamic rankings. LLM-as-a-judge evaluation employs stronger models to grade responses using predefined rubrics, offering scalable assessment of writing quality and reasoning that traditional metrics cannot capture.