mlsanityData to 7 Oct 2026

A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities

arXiv 2205.06743 ↗First posted 13 May 2022cs.LGcited by 162

Not on the map. Why?

Abstract (arXiv)

Few-shot learning (FSL) has emerged as an effective learning method and shows great potential. Despite the recent creative works in tackling FSL tasks, learning valid information rapidly from just a few or even zero samples still remains a serious challenge. In this context, we extensively investigated 200+ latest papers on FSL published in the past three years, aiming to present a timely and comprehensive overview of the most recent advances in FSL along with impartial comparisons of the strengths and weaknesses of the existing works. For the sake of avoiding conceptual confusion, we first elaborate and compare a set of similar concepts including few-shot learning, transfer learning, and meta-learning. Furthermore, we propose a novel taxonomy to classify the existing work according to the level of abstraction of knowledge in accordance with the challenges of FSL. To enrich this survey, in each subsection we provide in-depth analysis and insightful discussion about recent advances on these topics. Moreover, taking computer vision as an example, we highlight the important application of FSL, covering various research hotspots. Finally, we conclude the survey with unique insights into the technology evolution trends together with potential future research opportunities in the hope of providing guidance to follow-up research.

Key facts. Cited by 162 papers in the map (data through 7 Oct 2026). Builds on 258 of its 374 references that are in the map. First posted on arXiv 13 May 2022.

Builds on

258 of 374 references.

References · 258

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  4. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  5. 2020Language Models are Few-Shot Learnerscited by 32,199
  6. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  7. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  8. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
  9. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,339
  10. 2017mixup: Beyond Empirical Risk Minimizationcited by 5,155
  11. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,861
  12. 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,854
38 more
  1. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
  2. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,878
  3. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,827
  4. 2021The Power of Scale for Parameter-Efficient Prompt Tuningcited by 3,769
  5. 2017Prototypical Networks for Few-shot Learningcited by 3,001
  6. 2015Fast R-CNNcited by 2,930
  7. 2019A Comprehensive Survey on Graph Neural Networkscited by 2,906
  8. 2019CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Featurescited by 2,875
  9. 2018Deep contextualized word representationscited by 2,285
  10. 2021Learning to Prompt for Vision-Language Modelscited by 2,269
  11. 2016Matching Networks for One Shot Learningcited by 2,246
  12. 2013Describing Textures in the Wildcited by 2,110
  13. 2019Language Models as Knowledge Bases?cited by 1,922
  14. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,911
  15. 2018DARTS: Differentiable Architecture Searchcited by 1,782
  16. 2013Fine-Grained Visual Classification of Aircraftcited by 1,701
  17. 2017Improved Regularization of Convolutional Neural Networks with Cutoutcited by 1,623
  18. 2017EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classificationcited by 1,488
  19. 2020Making Pre-trained Language Models Better Few-shot Learnerscited by 1,255
  20. 2017Random Erasing Data Augmentationcited by 1,235
  21. 2019A Comprehensive Survey on Transfer Learningcited by 1,154
  22. 2017Learning to Compare: Relation Network for Few-Shot Learningcited by 1,139
  23. 2016Colorful Image Colorizationcited by 1,113
  24. 2018On First-Order Meta-Learning Algorithmscited by 1,003
  25. 2014Deep Visual-Semantic Alignments for Generating Image Descriptionscited by 966
  26. 2019How Can We Know What Language Models Know?cited by 953
  27. 2020Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inferencecited by 934
  28. 2018Efficient Neural Architecture Search via Parameter Sharingcited by 831
  29. 2019EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Taskscited by 800
  30. 2018AutoAugment: Learning Augmentation Policies from Datacited by 728
  31. 2021GPT Understands, Toocited by 715
  32. 2019A Closer Look at Few-shot Classificationcited by 679
  33. 2020It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learnerscited by 668
  34. 2019Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)cited by 657
  35. 2021Multimodal Few-Shot Learning with Frozen Language Modelscited by 657
  36. 2016Learning to learn by gradient descent by gradient descentcited by 616
  37. 2016StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networkscited by 575
  38. 2017Learning multiple visual domains with residual adapterscited by 553

50 most cited of 258 All 258 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 6; 2023: 34; 2024: 56; 2025: 46; 2026: 20.

162 papers.

Sort:

By area:

  1. 2024HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMscited by 257
  2. 2023CacheGen: KV Cache Compression and Streaming for Fast Large Language Model Servingcited by 199
  3. 2023Towards Open Vocabulary Learning: A Surveycited by 165
  4. 2024On the test-time zero-shot generalization of vision-language models: Do we really need prompt learning?cited by 65
  5. 2023A Survey on Few-Shot Class-Incremental Learningcited by 48
  6. 2024Reasoning Runtime Behavior of a Program with LLM: How Far Are We?cited by 44
  7. 2023A Survey on Deep Learning-Based Monocular Spacecraft Pose Estimation: Current State, Limitations and Prospectscited by 30
  8. 2023Learning Expressive Prompting With Residuals for Vision Transformerscited by 21
  9. 2023A Survey on the Robustness of Computer Vision Models against Common Corruptionscited by 20
  10. 2023SSTFormer: Bridging Spiking Neural Network and Memory Support Transformer for Frame-Event based Recognitioncited by 20
  11. 2024FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classificationcited by 20
  12. 2023BIRB: A Generalization Benchmark for Information Retrieval in Bioacousticscited by 19
38 more
  1. 2023The Hitchhiker's Guide to Program Analysis: A Journey with Large Language Modelscited by 18
  2. 2024Policy Adaptation via Language Optimization: Decomposing Tasks for Few-Shot Imitationcited by 18
  3. 2022Visual Semantic Segmentation Based on Few/Zero-Shot Learning: An Overviewcited by 16
  4. 2024A Comprehensive Survey of Convolutions in Deep Learning: Applications, Challenges, and Future Trendscited by 16
  5. 2023A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directionscited by 15
  6. 2023Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Surveycited by 14
  7. 2023A Survey on Stability of Learning with Limited Labelled Data and its Sensitivity to the Effects of Randomnesscited by 14
  8. 2024CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentationcited by 14
  9. 2023DVFO: Learning-Based DVFS for Energy-Efficient Edge-Cloud Collaborative Inferencecited by 13
  10. 2024Low-Resource Vision Challenges for Foundation Modelscited by 13
  11. 2024Enhancing Information Maximization with Distance-Aware Contrastive Learning for Source-Free Cross-Domain Few-Shot Learningcited by 13
  12. 2024Few-Shot Learning with Uncertainty-based Quadruplet Selection for Interference Classification in GNSS Datacited by 12
  13. 2024A Comprehensive Review of Few-shot Action Recognitioncited by 11
  14. 2025Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representationcited by 11
  15. 2025Logits DeConfusion with CLIP for Few-Shot Learningcited by 11
  16. 2024Learning by Watching: A Review of Video-based Learning Approaches for Robot Manipulationcited by 10
  17. 2023Image Synthesis under Limited Data: A Survey and Taxonomycited by 9
  18. 2024SAM-MPA: Applying SAM to Few-shot Medical Image Segmentation using Mask Propagation and Auto-promptingcited by 9
  19. 2025Exploring the Security Threats of Knowledge Base Poisoning in Retrieval-Augmented Code Generationcited by 9
  20. 2026SGAgent: Suggestion-Guided LLM-Based Multi-Agent Framework for Repository-Level Software Repaircited by 9
  21. 2024Enhancing Vision-Language Few-Shot Adaptation with Negative Learningcited by 8
  22. 2024Leveraging Latent Diffusion Models for Training-Free In-Distribution Data Augmentation for Surface Defect Detectioncited by 8
  23. 2024Brain-inspired Artificial Intelligence: A Comprehensive Reviewcited by 8
  24. 2024English Prompts are Better for NLI-based Zero-Shot Emotion Classification than Target-Language Promptscited by 7
  25. 2024Comprehensive Evaluation and Insights into the Use of Large Language Models in the Automation of Behavior-Driven Development Acceptance Test Formulationcited by 7
  26. 2024A Survey of Few-Shot Learning for Biomedical Time Seriescited by 7
  27. 2024QUITO: Accelerating Long-Context Reasoning through Query-Guided Context Compressioncited by 7
  28. 2024Demonstration Selection for In-Context Learning via Reinforcement Learningcited by 7
  29. 2025Small Models, Big Tasks: An Exploratory Empirical Study on Small Language Models for Function Callingcited by 7
  30. 2025Aligning LLM with human travel choices: a persona-based embedding learning approachcited by 7
  31. 2022Hierarchical Attention Network for Few-Shot Object Detection via Meta-Contrastive Learningcited by 6
  32. 2024Towards Incremental Learning in Large Language Models: A Critical Reviewcited by 6
  33. 2024TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characterscited by 6
  34. 2025Foundation models for time series forecasting: Application in conformal predictioncited by 6
  35. 2024Controllable Image Synthesis of Industrial Data Using Stable Diffusioncited by 5
  36. 2024A Survey of Few-Shot Learning on Graphs: from Meta-Learning to Pre-Training and Prompt Learningcited by 5
  37. 2024Few-shot Online Anomaly Detection and Segmentationcited by 5
  38. 2024MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlationcited by 5

50 most cited of 162 All 162 (JSON)