Human Evaluation & LLM-as-Judge

Summary

Using human raters, or another LLM prompted to score outputs, to evaluate quality dimensions automated metrics can't capture — like helpfulness, tone and factual correctness.

How to Learn This

1Design a simple rubric and manually evaluate a batch of model outputs against it.
2Try LLM-as-judge: prompt a strong model to score outputs against the same rubric.
3Learn LLM-as-judge's known biases (favoring longer or more confident-sounding answers).

LLM Evaluation Metrics (BLEU, ROUGE, Perplexity)

Bias & Fairness in AI

More topics in Evaluation, Safety & Responsible AI

LLM Evaluation Metrics (BLEU, ROUGE, Perplexity)Bias & Fairness in AI AI Safety Principles Guardrails & Content Moderation Hallucination Detection & Mitigation Explainable AI (XAI)Data Privacy in AI Systems Responsible AI Governance

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