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Poster
in
Workshop: MATH-AI: Toward Human-Level Mathematical Reasoning

Towards automating formalisation of theorem statements using large language models

Siddhartha Gadgil · Anand Tadipatri · Navin Goyal · Ayush Agrawal · Ashvni Narayanan


Abstract:

Mathematics formalisation is the task of writing mathematics (i.e., definitions, theorem statements, proofs) in natural language, as found in books and papers, into a formal language that can then be checked for correctness by a program. It is a thriving activity today, however formalisation remains cumbersome. In this paper, we explore the abilities of a large language model (Codex) to help with formalisation in the Lean theorem prover. We find that with careful input-dependent prompt selection and postprocessing, Codex is able to formalise short mathematical statements at undergrad level with nearly 75% accuracy for 120 theorem statements.

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