A taxonomy-guided ensemble of LLM judges correlates with human ratings of autoformalizations (up to 0.662 on Isabelle/HOL) better than coarse-grained judges and reference metrics, but validation is partly in-sample and the human gold standard is thin.
Improver: Agent-based auto- mated proof optimization
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Beyond Gold Standards: Epistemic Ensemble of LLM Judges for Formal Mathematical Reasoning
A taxonomy-guided ensemble of LLM judges correlates with human ratings of autoformalizations (up to 0.662 on Isabelle/HOL) better than coarse-grained judges and reference metrics, but validation is partly in-sample and the human gold standard is thin.