Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs

The formalization of existing mathematical proofs is a notoriously difficult process. Despite decades of research on automation and proof assistants, writing formal proofs remains arduous and only accessible to a few experts. While previous studies to automate formalization focused on powerful search algorithms, no attempts were made to take advantage of available informal proofs. In this work, we introduce Draft, Sketch, and Prove (DSP), a method that maps informal proofs to formal proof sketches, and uses the sketches to guide an automated prover by directing its search to easier sub-problems. We investigate two relevant setups where informal proofs are either written by humans or generated by a language model. Our experiments and ablation studies show that large language models are able to produce well-structured formal sketches that follow the same reasoning steps as the informal proofs. Guiding an automated prover with these sketches enhances its performance from 20.9% to 39.3% on a collection of mathematical competition problems.

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Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Automated Theorem Proving miniF2F-test DSP (540B Minerva informal) Pass@100 38.9 # 4
Automated Theorem Proving miniF2F-test Sledgehammer + heuristics Pass@1 20.9 # 10
Automated Theorem Proving miniF2F-valid DSP (62B Minerva informal) Pass@100 43.9 # 3

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