mlsanityData to 14 Oct 2026

A Survey on Evolutionary Neural Architecture Search

arXiv 2008.10937 ↗First posted 25 Aug 2020cs.NEcited by 142

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Abstract (arXiv)

Deep Neural Networks (DNNs) have achieved great success in many applications. The architectures of DNNs play a crucial role in their performance, which is usually manually designed with rich expertise. However, such a design process is labour intensive because of the trial-and-error process, and also not easy to realize due to the rare expertise in practice. Neural Architecture Search (NAS) is a type of technology that can design the architectures automatically. Among different methods to realize NAS, Evolutionary Computation (EC) methods have recently gained much attention and success. Unfortunately, there has not yet been a comprehensive summary of the EC-based NAS algorithms. This paper reviews over 200 papers of most recent EC-based NAS methods in light of the core components, to systematically discuss their design principles as well as justifications on the design. Furthermore, current challenges and issues are also discussed to identify future research in this emerging field.

Key facts. Cited by 142 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Aug 2020.

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Citing papers per year: 2021: 15; 2022: 26; 2023: 31; 2024: 32; 2025: 25; 2026: 13.

142 papers.

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  1. 2025Multi-agent Architecture Search via Agentic Supernetcited by 179
  2. 2023Neural Architecture Search: Insights from 1000 Paperscited by 139
  3. 2023Structured Pruning for Deep Convolutional Neural Networks: A surveycited by 122
  4. 2024A Survey on Self-Evolution of Large Language Modelscited by 91
  5. 2024Evolutionary Computation in the Era of Large Language Model: Survey and Roadmapcited by 90
  6. 2023LLMatic: Neural Architecture Search via Large Language Models and Quality Diversity Optimizationcited by 87
  7. 2024Model Compression and Efficient Inference for Large Language Models: A Surveycited by 64
  8. 2024Archon: An Architecture Search Framework for Inference-Time Techniquescited by 60
  9. 2021How to avoid machine learning pitfalls: a guide for academic researcherscited by 35
  10. 2023A Machine Learning-oriented Survey on Tiny Machine Learningcited by 27
  11. 2024DISP-LLM: Dimension-Independent Structural Pruning for Large Language Modelscited by 24
  12. 2023Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunitiescited by 21
38 more
  1. 2025DarwinLM: Evolutionary Structured Pruning of Large Language Modelscited by 18
  2. 2022Neural Architecture Search on Efficient Transformers and Beyondcited by 17
  3. 2024A Comprehensive Survey of Convolutions in Deep Learning: Applications, Challenges, and Future Trendscited by 16
  4. 2021AutoGL: A Library for Automated Graph Learningcited by 15
  5. 2023Zero-Shot Text-to-Parameter Translation for Game Character Auto-Creationcited by 15
  6. 2021SPIDER: Searching Personalized Neural Architecture for Federated Learningcited by 13
  7. 2021Half a Dozen Real-World Applications of Evolutionary Multitasking, and Morecited by 12
  8. 2022A Survey on Computationally Efficient Neural Architecture Searchcited by 12
  9. 2025Evolutionary Optimization of Physics-Informed Neural Networks: Evo-PINN Frontiers and Opportunitiescited by 11
  10. 2025A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solvingcited by 11
  11. 2021Accelerating Evolutionary Neural Architecture Search via Multi-Fidelity Evaluationcited by 10
  12. 2022FreeREA: Training-Free Evolution-based Architecture Searchcited by 10
  13. 2022Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and Directionscited by 9
  14. 2022A Survey on Evolutionary Computation for Computer Vision and Image Analysis: Past, Present, and Future Trendscited by 9
  15. 2024NACHOS: Neural Architecture Search for Hardware Constrained Early Exit Neural Networkscited by 9
  16. 2024FL-NAS: Towards Fairness of NAS for Resource Constrained Devices via Large Language Modelscited by 9
  17. 2023Explainable Knowledge Distillation for On-device Chest X-Ray Classificationcited by 8
  18. 2023Harmonic-NAS: Hardware-Aware Multimodal Neural Architecture Search on Resource-constrained Devicescited by 8
  19. 2023Plum: Prompt Learning using Metaheuristiccited by 8
  20. 2021Learning Deep Morphological Networks with Neural Architecture Searchcited by 6
  21. 2023EGANS: Evolutionary Generative Adversarial Network Search for Zero-Shot Learningcited by 6
  22. 2023TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly Detectioncited by 6
  23. 2024QCQA: Quality and Capacity-aware grouped Query Attentioncited by 6
  24. 2021Enhanced Gradient for Differentiable Architecture Searchcited by 5
  25. 2022POPNASv2: An Efficient Multi-Objective Neural Architecture Search Techniquecited by 5
  26. 2024A Framework for Strategic Discovery of Credible Neural Network Surrogate Models under Uncertaintycited by 5
  27. 2024Building Optimal Neural Architectures using Interpretable Knowledgecited by 5
  28. 2021Software/Hardware Co-design for Multi-modal Multi-task Learning in Autonomous Systemscited by 4
  29. 2021A Novel Evolutionary Algorithm for Hierarchical Neural Architecture Searchcited by 4
  30. 2022Towards Less Constrained Macro-Neural Architecture Searchcited by 4
  31. 2022Exploring the Intersection between Neural Architecture Search and Continual Learningcited by 4
  32. 2022AutoQML: Automatic Generation and Training of Robust Quantum-Inspired Classifiers by Using Genetic Algorithms on Grayscale Imagescited by 4
  33. 2022Genetic Programming-Based Evolutionary Deep Learning for Data-Efficient Image Classificationcited by 4
  34. 2022Pareto-aware Neural Architecture Generation for Diverse Computational Budgetscited by 4
  35. 2023A Comprehensive Review and a Taxonomy of Edge Machine Learning: Requirements, Paradigms, and Techniquescited by 4
  36. 2023Real-Time Semantic Segmentation: A Brief Survey & Comparative Study in Remote Sensingcited by 4
  37. 2024Unsupervised Domain Adaptation Architecture Search with Self-Training for Land Cover Mappingcited by 4
  38. 2024Automatic Graph Topology-Aware Transformercited by 4

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