What Can Large Language Models Do for Theorem Proving and Formal Methods?
Paper i 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.

Författare

Moa Johansson

Chalmers, Data- och informationsteknik, Data Science och 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,

Ämneskategorier

Språkteknologi (språkvetenskaplig databehandling)

Programvaruteknik

DOI

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

Mer information

Senast uppdaterat

2024-01-10