Explore/benchmark/Human-in-the-Loop Nugget Annotation for Accountable LLM-as-a-Judge Evaluations
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Laura Dietz/Human-in-the-Loop Nugget Annotation for Accountable LLM-as-a-Judge EvaluationsUnknown

Evaluating AI/Agentic system outputs reliably requires human judgment, but how one incorporates the human determines whether one gets a real quality signal or expensive theater. The common approaches either accidentally anchor human experts (leading to rubber-stamping) or leave them unsupported in high-variance labeling tasks. We present a prototype annotation tool that implements a different division of labor: humans identify what information matters (nuggets), while LLMs handle high-volume matching of nuggets to system outputs. This plays to each party's strengths while maintaining genuine human oversight. We describe the three-phase workflow, key design decisions, and how exported nugget banks integrate with automated judges.

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55 / 100
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58C
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2026-07-262026-10-10
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55
Score 55/100
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