PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition
Published in NeurIPS 2024 Datasets and Benchmarks Track, 2024
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.
Recommended citation: George Tsoukalas, Jasper Lee, John Jennings, Jimmy Xin, Michelle Ding, Michael Jennings, Amitayush Thakur, and Swarat Chaudhuri. PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition. In NeurIPS 2024 Datasets and Benchmarks Track, 2024. URL https://openreview.net/forum?id=ChKCF75Ocd.
Download Paper