How to Use LLM as a Judge (Without Getting Burned) - Manthan
TL;DR: LLM as a judge works well when you (1) use reference based evaluation over pointwise scoring, (2) debias pairwise comparisons by swapping positions, (3) ensemble across multiple models, (4) require reasoning before scores, and (5) calibrate against human judgments. Skip it when ground truth exists or for safety critical decisions. Table of Contents Why Traditional Evaluation Methods Fail Evaluation Modes Crafting Effective Judge Prompts Limitations and Biases When NOT to Use LLM as a judge Optimizations Conclusion Last month, I ran thousands of evals on an agentic system I was building. The responses were open-ended, context dependent, and impossible to validate with simple string matching. I tried exact match comparisons, they failed miserably. I tried BLEU scores, they penalized semantically correct but differently worded responses. I was stuck! Traditional metrics could not handle the nuance I needed, and manual evaluation was too slow and expensive.
TL;DR: LLM as a judge works well when you (1) use reference based evaluation over pointwise scoring, (2) debias pairwise comparisons by swapping positions, (3) ensemble across multiple models, (4) require reasoning before scores, and (5) calibrate against human judgments. Skip it when ground truth exists or for safety critical decisions. Table of Contents Why Traditional Evaluation Methods Fail Evaluation Modes Crafting Effective Judge Prompts Limitations and Biases When NOT to Use LLM as a judge Optimizations Conclusion Last month, I ran thousands of evals on an agentic system I…
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