Search Results for author:
Found 5 papers, 3 papers with code
Formal Mathematics Statement Curriculum Learning
We explore the use of expert iteration in the context of language modeling applied to formal mathematics.
Ranked #3 on
Automated Theorem Proving
on miniF2F-test
(using extra training data)
Unsupervised Neural Machine Translation with Generative Language Models Only
We show how to derive state-of-the-art unsupervised neural machine translation systems from generatively pre-trained language models.
MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics
We present miniF2F, a dataset of formal Olympiad-level mathematics problems statements intended to provide a unified cross-system benchmark for neural theorem proving.
Ranked #1 on
Automated Theorem Proving
on miniF2F-valid
(using extra training data)
Proof Artifact Co-training for Theorem Proving with Language Models
Labeled data for imitation learning of theorem proving in large libraries of formalized mathematics is scarce as such libraries require years of concentrated effort by human specialists to be built.
Ranked #7 on
Automated Theorem Proving
on miniF2F-test
Generative Language Modeling for Automated Theorem Proving
We explore the application of transformer-based language models to automated theorem proving.
Ranked #1 on
Automated Theorem Proving
on Metamath set.mm
