mlsanityData to 7 Oct 2026

Hammering Mizar by Learning Clause Guidance

arXiv 1904.01677 ↗First posted 2 Apr 2019cs.AI cs.LG cs.LOcited by 20

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Abstract (arXiv)

We describe a very large improvement of existing hammer-style proof automation over large ITP libraries by combining learning and theorem proving. In particular, we have integrated state-of-the-art machine learners into the E automated theorem prover, and developed methods that allow learning and efficient internal guidance of E over the whole Mizar library. The resulting trained system improves the real-time performance of E on the Mizar library by 70% in a single-strategy setting.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Apr 2019.

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Citing papers per year: 2021: 8; 2022: 1; 2023: 3; 2024: 5; 2025: 3.

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