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Modern DAG exchangeability in probabilistic AI is secretly classical algebraic design theory, mapping graph-structured de Finetti representations directly onto generalized wreath products.
LLMs achieve higher agreement with examiners than the examiners do with each other, challenging traditional assumptions about human grading reliability.