mlsanityData to 7 Oct 2026

Language Model Crossover: Variation through Few-Shot Prompting

arXiv 2302.12170 ↗First posted 23 Feb 2023cs.NEcited by 119

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Abstract (arXiv)

This paper pursues the insight that language models naturally enable an intelligent variation operator similar in spirit to evolutionary crossover. In particular, language models of sufficient scale demonstrate in-context learning, i.e. they can learn from associations between a small number of input patterns to generate outputs incorporating such associations (also called few-shot prompting). This ability can be leveraged to form a simple but powerful variation operator, i.e. to prompt a language model with a few text-based genotypes (such as code, plain-text sentences, or equations), and to parse its corresponding output as those genotypes' offspring. The promise of such language model crossover (which is simple to implement and can leverage many different open-source language models) is that it enables a simple mechanism to evolve semantically-rich text representations (with few domain-specific tweaks), and naturally benefits from current progress in language models. Experiments in this paper highlight the versatility of language-model crossover, through evolving binary bit-strings, sentences, equations, text-to-image prompts, and Python code. The conclusion is that language model crossover is a promising method for evolving genomes representable as text.

Key facts. Cited by 119 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Feb 2023.

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Citing papers per year: 2023: 12; 2024: 36; 2025: 42; 2026: 29.

119 papers.

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  1. 2023Large Language Models as Optimizerscited by 830
  2. 2023Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolutioncited by 521
  3. 2024Automated Design of Agentic Systemscited by 360
  4. 2024ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolutioncited by 266
  5. 2024Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Modelcited by 258
  6. 2023EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizerscited by 189
  7. 2024Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Promptscited by 189
  8. 2023EvoPrompting: Language Models for Code-Level Neural Architecture Searchcited by 129
  9. 2024Large Language Models to Enhance Bayesian Optimizationcited by 127
  10. 2024LLM-SR: Scientific Equation Discovery via Programming with Large Language Modelscited by 117
  11. 2025Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Designcited by 100
  12. 2024Evolutionary Computation in the Era of Large Language Model: Survey and Roadmapcited by 89
38 more
  1. 2024Open-Endedness is Essential for Artificial Superhuman Intelligencecited by 79
  2. 2024Symbolic Regression with a Learned Concept Librarycited by 76
  3. 2024HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven Harmony Search and Genetic Algorithm Using LLMscited by 68
  4. 2023Algorithm Evolution Using Large Language Modelcited by 52
  5. 2025Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimizationcited by 52
  6. 2024Evolving Code with A Large Language Modelcited by 42
  7. 2023Quality-Diversity through AI Feedbackcited by 40
  8. 2025LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizerscited by 35
  9. 2025The Homogenizing Effect of Large Language Models on Human Expression and Thoughtcited by 35
  10. 2025Self-Improving Language Models for Evolutionary Program Synthesis: A Case Study on ARC-AGIcited by 34
  11. 2024Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Modelscited by 31
  12. 2023Large Language Model for Multi-objective Evolutionary Optimizationcited by 29
  13. 2024Evolutionary Large Language Model for Automated Feature Transformationcited by 29
  14. 2025Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learningcited by 28
  15. 2024LICO: Large Language Models for In-Context Molecular Optimizationcited by 26
  16. 2024FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearchcited by 22
  17. 2024Understanding the Importance of Evolutionary Search in Automated Heuristic Design with Large Language Modelscited by 22
  18. 2024Position: Leverage Foundational Models for Black-Box Optimizationcited by 21
  19. 2023Generative Calibration for In-context Learningcited by 20
  20. 2024When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challengescited by 20
  21. 2025DrSR: LLM based Scientific Equation Discovery with Dual Reasoning from Data and Experiencecited by 20
  22. 2023Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systemscited by 18
  23. 2023An evolutionary model of personality traits related to cooperative behavior using a large language modelcited by 18
  24. 2025Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMscited by 15
  25. 2025CoCoEvo: Co-Evolution of Programs and Test Cases to Enhance Code Generationcited by 14
  26. 2024Pretrained Optimization Model for Zero-Shot Black Box Optimizationcited by 13
  27. 2024How Multimodal Integration Boost the Performance of LLM for Optimization: Case Study on Capacitated Vehicle Routing Problemscited by 12
  28. 2024Deep Insights into Automated Optimization with Large Language Models and Evolutionary Algorithmscited by 12
  29. 2025Tricking Retrievers with Influential Tokens: An Efficient Black-Box Corpus Poisoning Attackcited by 9
  30. 2025A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solvingcited by 9
  31. 2024ICE-SEARCH: A Language Model-Driven Feature Selection Approachcited by 8
  32. 2024From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language Modelscited by 8
  33. 2024Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization Taskscited by 8
  34. 2025Optimizing Diversity and Quality through Base-Aligned Model Collaborationcited by 8
  35. 2024Large Language Models as In-context AI Generators for Quality-Diversitycited by 7
  36. 2024Grammar-based Game Description Generation using Large Language Modelscited by 7
  37. 2024In Context Learning and Reasoning for Symbolic Regression with Large Language Modelscited by 7
  38. 2024LLM-Virus: Evolutionary Jailbreak Attack on Large Language Modelscited by 7

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