Neural Theorem Proving in Lean using Proof Artifact Co|training and ...

Proof Artifact Co-training for Theorem Proving with Language Models

We instrument Lean with a neural theorem prover driven by a Transformer language model and show that PACT improves theorem proving success rate.

Proof Artifact Co-Training for Theorem Proving with Language Models

One-sentence Summary: Co-training on low-level proof tasks in a Transformer theorem prover improves success from 32% to 48% on Lean theorems.

Neural Theorem Proving in Lean using Proof Artifact Co-training and ...

Neural Theorem Proving in Lean using Proof Artifact Co-training and Language Models · Speakers · Organizer · About ICLR 2021 · Like the format? Trust SlidesLive to ...

PROOF ARTIFACT CO-TRAINING FOR THEOREM PROV

We instrument Lean with a neural theorem prover driven by a Transformer ... However, existing datasets of human proof steps for neural theorem proving are ...

Proof Artifact Co-Training for Theorem Proving with Language Models

... Lean, an interactive proof assistant which hosts some of the most sophisticated formalized mathematics to date. We instrument Lean with a neural theorem.

proof artifact co-training for theorem prov - arXiv

We instrument Lean with a neural theorem prover driven by a Transformer language model and show that PACT improves theorem proving success ...

Proof Artifact Co-training for Theorem Proving with Language Models

102 Citations · Synthetic Proof Term Data Augmentation for Theorem Proving with Language Models · Lean-STaR: Learning to Interleave Thinking and Proving · Thor: ...

jesse-michael-han/lean-step-public: Proof artifact co-training for Lean

Proof artifact co-training for Lean. Contribute to jesse-michael-han/lean-step-public development by creating an account on GitHub.

PROOF ARTIFACT CO-TRAINING FOR THEOREM PROV - MATH-AI

and a machine learning environment for the Lean 3 theorem prover with support for PACT, supervised learning of tactic prediction, theorem proving evaluation, ...

Neural theorem proving - Sean Welleck

LeanDojo: Theorem Proving with Retrieval-Augmented Language Models. Yang ... Proof Artifact Co-training for Theorem Proving with Language Models. Han ...

Contributions to Neural Theorem Proving - D-Scholarship@Pitt

... proof artifact which is verified by Lean's ... using proof artifacts. 3.1 Proof artifact co-training for theorem proving with language models.

Proof Artifact Co-training for Theorem Proving with Language Models

We instrument Lean with a neural theorem prover driven by a ...

Theorem Proving with Retrieval-Augmented Language Models

It also enables the trained model to prove theorems by interacting with Lean's proof ... For example, Proof Artifact Co-Training. (PACT) co-trains the tactic ...

Deep Learning for Theorem Proving (DL4TP) - GitHub

... Neural Theorem Proving IJCAI 2023 Tutorial [link] [Lean ... Proof Artifact Co-Training for Theorem Proving with Language Models ICLR 2022 [paper] [Lean].

miniCTX: Neural Theorem Proving with (Long-)Contexts

Leanaide. https://github.com/siddhartha-gadgil/LeanAide, 2024. [4] J. M. Han, J. Rute, Y. Wu, E. Ayers, and S. Polu. Proof artifact co-training for theorem ...

"PACT: Proof Artifact Co-training for Theorem Proving with ... - Reddit

46K subscribers in the reinforcementlearning community. Reinforcement learning is a subfield of AI/statistics focused on exploring/understanding…

Automated Theorem Proving | Papers With Code

Automated Theorem Proving · Holophrasm: a neural Automated Theorem Prover for higher-order logic · Proof Artifact Co-training for Theorem Proving with Language ...

Data Sets for Machine Learning for Mathematical Formalization

We instrument Lean with a neural theorem prover driven by a Transformer language model and show that PACT improves theorem proving success rate on a held-out ...

HyperTree proof search for neural theorem proving

Online training on these unproved theorems increases accuracy to 82.6%. With a similar computational budget, we improve the state of the art on ...

Proof Artifact Co-training for Theorem Proving with Language ...

Their idea is to use proof objects to create a number of auxiliary tasks, which all benefit from the uniformity of training language models for different tasks.