Metric Match: A Subset Selection Approach to Evaluating LLM Judge Reliability
LLM judges are used to reduce the need for costly human labor in evaluating open-ended text generation. However, the reliability of these judges depends critically on their alignment with human raters -- a property that itself depends on costly human annotations. In this work, we develop a method (Metric Match) for estimating correlation-based reliability metrics of LLM judges from limited annotations. Metric Match selects a subset of samples for human annotation such that the subset matches the
Record details
Published: 12 June 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Jobs & economy
Retrieved: 14 July 2026
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ethics.ai (12 June 2026), “Metric Match: A Subset Selection Approach to Evaluating LLM Judge Reliability,” evidence record 1040, https://ethics.ai/record/1040 (originally published by arXiv).
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