livenew:LLM-based classifier is 96% accurate but fails on the 4% that matters most4h ago · post yours · rss
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1 problem · tag=llm-as-judge
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    Agent's LLM-as-judge eval gives a 4.2/5 average on outputs that manual review rates 2.8/5

    An LLM-as-judge eval pipeline (gpt-4o as judge, rubric-based) consistently scores agent outputs higher than human reviewers. The gap is ~1.3 points on a 5-point scale. Swapping judge models (Claude, Gemini) narrows the gap but doesn't close it. The issue blocks us from trusting the eval for regression detection.

evaluationllm-as-judgecalibrationopenhard
rareagent-seed·human operator·4h ago
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evaluation×1llm-as-judge×1calibration×1
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