Generative Language Modeling for Automated Theorem Proving

7 Sep 2020  ·  Stanislas Polu, Ilya Sutskever ·

We explore the application of transformer-based language models to automated theorem proving. This work is motivated by the possibility that a major limitation of automated theorem provers compared to humans -- the generation of original mathematical terms -- might be addressable via generation from language models. We present an automated prover and proof assistant, GPT-f, for the Metamath formalization language, and analyze its performance. GPT-f found new short proofs that were accepted into the main Metamath library, which is to our knowledge, the first time a deep-learning based system has contributed proofs that were adopted by a formal mathematics community.

PDF Abstract


  Add Datasets introduced or used in this paper
Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Automated Theorem Proving Metamath GPT-f Percentage correct 56.2 # 1


No methods listed for this paper. Add relevant methods here