LLMs as Judges: Using Large Language Models to Evaluate AI-Generated Text
LLMs as Judges: Using Large Language Models to Evaluate AI-Generated Text 1. Introduction The Challenge of Evaluating AI-Generated Text Imagine you’re a teacher grading thousands of essays, or a company evaluating customer service responses generated by AI. How do you determine which responses are good, which are bad, and which need improvement? This is one of the biggest challenges in artifical intelligence today. Traditionally, researchers have used mathematical formulas (called metrics like BLEU and ROUGE) to automatically score text. Think of these like spell-checkers – they can catch obvious errors, but they can’t tell if a piece of writing is truly engaging, accurate, or helpful. These traditional methods often miss the nuances that make text truly good: Does it flow naturally? Is it factually correct? Does it actually answer the question asked? ...