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The Geometry of LLM-as-Judge: Why Inter-LLM Consensus Is Not Human Alignment
LLM judges now score most open-ended NLP output, and their mutual agreement is routinely read as evidence that the scores can be trusted. That reading is unsafe: judges may agree because they capture quality, or because they share the same blind spots, and agreement statistics alone cannot tell thes
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