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Albert Qiaochu Jiang

3 accepted papers

2023

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

ICLR 2023top-5%

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 searc…

Cited by 172SourcePDFScholar
2022

Autoformalization with Large Language Models

NeurIPS 2022accept

Autoformalization is the process of automatically translating from natural language mathematics to formal specifications and proofs. A successful autoformalization system could advance the fields of formal verification, program synthesis, and artificial intelligence. While the long-term goal of auto…

Cited by 189SourcePDFScholar
2022

Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers

NeurIPS 2022accept

In theorem proving, the task of selecting useful premises from a large library to unlock the proof of a given conjecture is crucially important. This presents a challenge for all theorem provers, especially the ones based on language models, due to their relative inability to reason over huge volume…

Cited by 104SourcePDFScholar