What Can Large Language Models Do forĀ Theorem Proving andĀ Formal Methods?
Paper in proceeding, 2024

With the introduction of large language models, AI for natural language have taken a leap. These systems are now also being used for tasks that has previously been dominated by symbolic methods, such as program synthesis and even to support formalising mathematics and assist theorem provers. We survey some recent applications in theorem proving, focusing on how they combine neural networks with symbolic systems, and report on a case-study of using GPT-4 for the task of automated conjecturing a.k.a. theory exploration.

Author

Moa Johansson

Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 14380 LNCS 391-394
9783031460012 (ISBN)

1st International Conference on Bridging the Gap between AI and Reality, AISoLA 2023
Crete, Greece,

Subject Categories

Language Technology (Computational Linguistics)

Software Engineering

DOI

10.1007/978-3-031-46002-9_25

More information

Latest update

1/10/2024