About
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
Benchmarks
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Datasets
Greatest papers with code
HOList: An Environment for Machine Learning of Higher-Order Theorem Proving
We present an environment, benchmark, and deep learning driven automated theorem prover for higher-order logic.
Ranked #2 on
Automated Theorem Proving
on HOList benchmark
HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving
We propose various machine learning tasks that can be performed on this dataset, and discuss their significance for theorem proving.
Ranked #3 on
Automated Theorem Proving
on HolStep (Unconditional)
Learning to Prove Theorems via Interacting with Proof Assistants
Proof assistants offer a formalism that resembles human mathematical reasoning, representing theorems in higher-order logic and proofs as high-level tactics.
Ranked #1 on
Automated Theorem Proving
on CoqGym
On-demand Injection of Lexical Knowledge for Recognising Textual Entailment
We approach the recognition of textual entailment using logical semantic representations and a theorem prover.
AUTOMATED THEOREM PROVING INFORMATION RETRIEVAL NATURAL LANGUAGE INFERENCE QUESTION ANSWERING
Learning as Abduction: Trainable Natural Logic Theorem Prover for Natural Language Inference
Tackling Natural Language Inference with a logic-based method is becoming less and less common.
LangPro: Natural Language Theorem Prover
LangPro is an automated theorem prover for natural language (https://github. com/kovvalsky/LangPro).
GamePad: A Learning Environment for Theorem Proving
In this paper, we introduce a system called GamePad that can be used to explore the application of machine learning methods to theorem proving in the Coq proof assistant.
G2SAT: Learning to Generate SAT Formulas
NeurIPS 2019
• JiaxuanYou/G2SAT
• 
The Boolean Satisfiability (SAT) problem is the canonical NP-complete problem and is fundamental to computer science, with a wide array of applications in planning, verification, and theorem proving.
Holophrasm: a neural Automated Theorem Prover for higher-order logic
I propose a system for Automated Theorem Proving in higher order logic using deep learning and eschewing hand-constructed features.
Ranked #3 on
Automated Theorem Proving
on Metamath set.mm