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Solving olympiad geometry without human demonstrations | Nature

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Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Advertisement Nature volume 625, pages 476–482 (2024)Cite this article 241k Accesses 13 Citations 973 Altmetric Metrics details An Author Correction to this article was published on 23 February 2024 This article has been updated Proving mathematical theorems at the olympiad level represents a notable milestone in human-level automated reasoning1,2,3,4, owing to their reputed difficulty among the world’s best talents in pre-university mathematics. Current machine-learning approaches, however, are not applicable to most mathematical domains owing to the high cost of translating human proofs into machine-verifiable format.

Download PDF Subjects Computational science Computer science An Author Correction to this article was published on 23 February 2024 This article has been updated Abstract Proving mathematical theorems at the olympiad level represents a notable milestone in human-level automated reasoning 1 , 2 , 3 , 4 , owing to their reputed difficulty among the world’s best talents in pre-university mathematics. Current machine-learning approaches, however, are not applicable to most mathematical domains owing to the high cost of translating human proofs into machine-verifiable format. The problem is even wo

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