Search Results for author:
Found 8 papers, 6 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)
Text and Code Embeddings by Contrastive Pre-Training
Similarly to text embeddings, we train code embedding models on (text, code) pairs, obtaining a 20. 8% relative improvement over prior best work on code search.
Ranked #1 on
Passage Ranking
on MS MARCO
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
Universal Policies for Software-Defined MDPs
We introduce a new programming paradigm called oracle-guided decision programming in which a program specifies a Markov Decision Process (MDP) and the language provides a universal policy.
Enhancing SAT solvers with glue variable predictions
Modern SAT solvers routinely operate at scales that make it impractical to query a neural network for every branching decision.
A formalization of forcing and the unprovability of the continuum hypothesis
We describe a formalization of forcing using Boolean-valued models in the Lean 3 theorem prover, including the fundamental theorem of forcing and a deep embedding of first-order logic with a Boolean-valued soundness theorem.
Logic in Computer Science Logic 03-04, 03E35, 03E40
