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.

TREND DATASET BEST METHOD PAPER TITLE PAPER CODE COMPARE

# HOList: An Environment for Machine Learning of Higher-Order Theorem Proving

5 Apr 2019tensorflow/deepmath

We present an environment, benchmark, and deep learning driven automated theorem prover for higher-order logic.

751

# HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving

1 Mar 2017tensorflow/deepmath

We propose various machine learning tasks that can be performed on this dataset, and discuss their significance for theorem proving.

751

# Learning to Prove Theorems via Interacting with Proof Assistants

21 May 2019princeton-vl/CoqGym

Proof assistants offer a formalism that resembles human mathematical reasoning, representing theorems in higher-order logic and proofs as high-level tactics.

195

# 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.

165

127

# Learning as Abduction: Trainable Natural Logic Theorem Prover for Natural Language Inference

29 Oct 2020kovvalsky/LangPro

Tackling Natural Language Inference with a logic-based method is becoming less and less common.

77

# LangPro: Natural Language Theorem Prover

LangPro is an automated theorem prover for natural language (https://github. com/kovvalsky/LangPro).

77

# 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.

65

# G2SAT: Learning to Generate SAT Formulas

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.

29

# Holophrasm: a neural Automated Theorem Prover for higher-order logic

8 Aug 2016dwhalen/holophrasm

I propose a system for Automated Theorem Proving in higher order logic using deep learning and eschewing hand-constructed features.

26