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Automated Theorem Proving
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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
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Automated Planning Techniques for Elementary Proofs in Abstract Algebra
Large Language Models' Understanding of Math: Source Criticism and Extrapolation
Generative Learning of Continuous Data by Tensor Networks
math-PVS: A Large Language Model Framework to Map Scientific Publications to PVS Theories
TRIGO: Benchmarking Formal Mathematical Proof Reduction for Generative Language Models
Llemma: An Open Language Model For Mathematics
An In-Context Learning Agent for Formal Theorem-Proving
LEGO-Prover: Neural Theorem Proving with Growing Libraries
Lyra: Orchestrating Dual Correction in Automated Theorem Proving
The Mathematical Game
FIMO: A Challenge Formal Dataset for Automated Theorem Proving
Math Agents: Computational Infrastructure, Mathematical Embedding, and Genomics
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
Decomposing the Enigma: Subgoal-based Demonstration Learning for Formal Theorem Proving
Theorem Proving in Dependently-Typed Higher-Order Logic -- Extended Preprint
An Ensemble Approach for Automated Theorem Proving Based on Efficient Name Invariant Graph Neural Representations
Translating SUMO-K to Higher-Order Set Theory
Planning as Theorem Proving with Heuristics
Probabilistic unifying relations for modelling epistemic and aleatoric uncertainty: semantics and automated reasoning with theorem proving
Can neural networks do arithmetic? A survey on the elementary numerical skills of state-of-the-art deep learning models
Lemmas: Generation, Selection, Application
Proceedings 11th International Workshop on Theorem Proving Components for Educational Software
Magnushammer: A Transformer-Based Approach to Premise Selection
ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics
Anti-unification and Generalization: A Survey
EuclidNet: Deep Visual Reasoning for Constructible Problems in Geometry
Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions
Solving Quantified Modal Logic Problems by Translation to Classical Logics
Peano: Learning Formal Mathematical Reasoning
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs
Generating Compressed Combinatory Proof Structures -- An Approach to Automated First-Order Theorem Proving
Proceedings 38th International Conference on Logic Programming
CD Tools -- Condensed Detachment and Structure Generating Theorem Proving (System Description)
Learning to Prove Trigonometric Identities
Exploring Length Generalization in Large Language Models
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