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Cost-Effective Automated Judging of Natural-Language Mathematical Proofs

Grayzel, Benjamin
arXiv (All) · Papers
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computation-and-languagemachine-learning
Grading natural-language mathematical proofs is a recurring cost in evaluating math-reasoning systems, and frontier LLM judges are expensive. We ask whether cheap open-weight models can serve as reliable judges given a candidate proof, a ground-truth proof, and a human-grading rubric. On a 200-insta
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