mlsanityData to 7 Oct 2026

Enhancing Genetic Improvement Mutations Using Large Language Models

arXiv 2310.19813 ↗First posted 18 Oct 2023cs.SE cs.AI cs.LGcited by 12

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Abstract (arXiv)

Large language models (LLMs) have been successfully applied to software engineering tasks, including program repair. However, their application in search-based techniques such as Genetic Improvement (GI) is still largely unexplored. In this paper, we evaluate the use of LLMs as mutation operators for GI to improve the search process. We expand the Gin Java GI toolkit to call OpenAI's API to generate edits for the JCodec tool. We randomly sample the space of edits using 5 different edit types. We find that the number of patches passing unit tests is up to 75% higher with LLM-based edits than with standard Insert edits. Further, we observe that the patches found with LLMs are generally less diverse compared to standard edits. We ran GI with local search to find runtime improvements. Although many improving patches are found by LLM-enhanced GI, the best improving patch was found by standard GI.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 7 of its 17 references that are in the map. First posted on arXiv 18 Oct 2023.

Builds on

7 of 17 references.

References · 7

  1. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  2. 2023Large Language Models for Software Engineering: A Systematic Literature Reviewcited by 389
  3. 2023Keep the Conversation Going: Fixing 162 out of 337 bugs for 0.42 each using ChatGPTcited by 125
  4. 2023An Analysis of the Automatic Bug Fixing Performance of ChatGPTcited by 108
  5. 2023Fuzz4All: Universal Fuzzing with Large Language Modelscited by 88
  6. 2023Inductive reasoning in humans and large language modelscited by 23
  7. 2023Towards Objective-Tailored Genetic Improvement Through Large Language Modelscited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 7; 2025: 3; 2026: 1.

12 papers.

  1. 2024Evolutionary Computation in the Era of Large Language Model: Survey and Roadmapcited by 89
  2. 2023Algorithm Evolution Using Large Language Modelcited by 52
  3. 2024Search-Based LLMs for Code Optimizationcited by 27
  4. 2024When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challengescited by 20
  5. 2024How Multimodal Integration Boost the Performance of LLM for Optimization: Case Study on Capacitated Vehicle Routing Problemscited by 12
  6. 2024It's Morphing Time: Unleashing the Potential of Multiple LLMs via Multi-objective Optimizationcited by 10
  7. 2024Geneverse: A collection of Open-source Multimodal Large Language Models for Genomic and Proteomic Researchcited by 8
  8. 2024LLM-Virus: Evolutionary Jailbreak Attack on Large Language Modelscited by 7
  9. 2025Decision Tree Induction Through LLMs via Semantically-Aware Evolutioncited by 6
  10. 2025Can Large Language Models Be Trusted as Evolutionary Optimizers for Network-Structured Combinatorial Problems?cited by 3
  11. 2025Structure-Aware Cooperative Ensemble Evolutionary Optimization on Combinatorial Problems with Multimodal Large Language Modelscited by 0
  12. 2026The New Compiler Stack: A Survey on the Synergy of LLMs and Compilerscited by 0