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PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition

PutnamBench evaluates neural theorem-provers on solving formalized competition mathematics problems, demonstrating the challenge for research in neural theorem-proving.

Year
2024
Venue
arXiv 2024
Authors
8
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arxiv.org/abs/2407.11214v2ARXIV-DEFAULT
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Abstract

We present PutnamBench, a new multi-language benchmark for evaluating the ability of neural theorem-provers to solve competition mathematics problems. PutnamBench consists of 1692 hand-constructed formalizations of 640 theorems sourced from the William Lowell Putnam Mathematical Competition, the premier undergraduate-level mathematics competition in North America. All the problems have formalizations in Lean 4 and Isabelle; a substantial subset also has Coq formalizations. PutnamBench requires significant problem-solving ability and proficiency in a broad range of topics taught in undergraduate mathematics courses. We use PutnamBench to evaluate several established neural and symbolic theorem-provers. These approaches can only solve a handful of the PutnamBench problems, establishing the benchmark as a difficult open challenge for research on neural theorem-proving. PutnamBench is available at https://github.com/trishullab/PutnamBench.

Authors

8