miscellaneous-6
Automated Theorem Proving
3260 papers • 126 benchmarks • 313 datasets
The goal of Automated Theorem Proving is to automatically generate a proof, given a conjecture (the target theorem) and a knowledge base of known facts, all expressed in a formal language. Automated Theorem Proving is useful in a wide range of applications, including the verification and synthesis of software and hardware systems. Source: Learning to Prove Theorems by Learning to Generate Theorems
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Benchmarks
These leaderboards are used to track progress in automated-theorem-proving-18
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Actions
miniF2F-test
miniF2F-test
miniF2F-valid
miniF2F-valid
HolStep (Conditional)
Libraries
iUse these libraries to find automated-theorem-proving-18 models and implementations
2 papers 6,434
Datasets
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Most implemented papers
Holophrasm: a neural Automated Theorem Prover for higher-order logic
Daniel Whalen•Sun Aug 07 2016
Holophrasm exploits the formalism of the Metamath language and explores partial proof trees using a neural-network-augmented bandit algorithm and a sequence-to-sequence model for action enumeration.
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