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Meta-learning approaches for few-shot learning: A survey of recent advances

arXiv 2303.07502 ↗First posted 13 Mar 2023cs.LG cs.AIcited by 25

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Abstract (arXiv)

Despite its astounding success in learning deeper multi-dimensional data, the performance of deep learning declines on new unseen tasks mainly due to its focus on same-distribution prediction. Moreover, deep learning is notorious for poor generalization from few samples. Meta-learning is a promising approach that addresses these issues by adapting to new tasks with few-shot datasets. This survey first briefly introduces meta-learning and then investigates state-of-the-art meta-learning methods and recent advances in: (I) metric-based, (II) memory-based, (III), and learning-based methods. Finally, current challenges and insights for future researches are discussed.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 71 of its 134 references that are in the map. First posted on arXiv 13 Mar 2023.

Builds on

71 of 134 references.

References · 71

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  2. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,861
  3. 2017Prototypical Networks for Few-shot Learningcited by 3,001
  4. 2016Matching Networks for One Shot Learningcited by 2,246
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  6. 2017Learning to Compare: Relation Network for Few-Shot Learningcited by 1,139
  7. 2018On First-Order Meta-Learning Algorithmscited by 1,003
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38 more
  1. 2019Meta-Learning with Differentiable Convex Optimizationcited by 461
  2. 2018Meta-Learning for Semi-Supervised Few-Shot Classificationcited by 456
  3. 2018Conditional Neural Processescited by 421
  4. 2018Meta-learning with differentiable closed-form solverscited by 395
  5. 2018Dynamic Few-Shot Visual Learning without Forgettingcited by 385
  6. 2017Meta-SGD: Learning to Learn Quickly for Few-Shot Learningcited by 377
  7. 2017A simple neural network module for relational reasoningcited by 345
  8. 2017Few-Shot Learning with Graph Neural Networkscited by 324
  9. 2019Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examplescited by 312
  10. 2018Meta-Transfer Learning for Few-Shot Learningcited by 306
  11. 2020A Brief Review of Domain Adaptationcited by 287
  12. 2017Meta Networkscited by 268
  13. 2018Probabilistic Model-Agnostic Meta-Learningcited by 254
  14. 2018Bayesian Model-Agnostic Meta-Learningcited by 194
  15. 2018Recasting Gradient-Based Meta-Learning as Hierarchical Bayescited by 180
  16. 2018Task-Agnostic Meta-Learning for Few-shot Learningcited by 151
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  25. 2019Generating Classification Weights with GNN Denoising Autoencoders for Few-Shot Learningcited by 69
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  27. 2018Incremental Few-Shot Learning with Attention Attractor Networkscited by 65
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  38. 2019TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learningcited by 32

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 15; 2026: 7.

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  1. 2024Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomycited by 16
  2. 2024A Comprehensive Review of Few-shot Action Recognitioncited by 11
  3. 2025Deep Learning in Concealed Dense Predictioncited by 6
  4. 2025Generalization-Enhanced Few-Shot Object Detection in Remote Sensingcited by 4
  5. 2025Data-Efficient Hate Speech Detection via Cross-Lingual Nearest Neighbor Retrieval with Limited Labeled Datacited by 2
  6. 2025Fusing Cross-Domain Knowledge from Multimodal Data to Solve Problems in the Physical Worldcited by 2
  7. 2024STAND: Self-Aware Precondition Induction for Interactive Task Learningcited by 1
  8. 2025TMetaNet: Topological Meta-Learning Framework for Dynamic Link Predictioncited by 1
  9. 2025IDRBench: Understanding the Capability of Large Language Models on Interdisciplinary Researchcited by 1
  10. 2025CCoMAML: Efficient Cattle Identification Using Cooperative Model-Agnostic Meta-Learningcited by 1
  11. 2025Meta-Learning Linear Models for Molecular Property Predictioncited by 1
  12. 2025Riemannian Geometric-based Meta Learningcited by 0
13 more
  1. 2025FACE: Few-shot Adapter with Cross-view Fusion for Cross-subject EEG Emotion Recognitioncited by 0
  2. 2025Enhancing Trust Management System for Connected Autonomous Vehicles Using Machine Learning Methods: A Surveycited by 0
  3. 2025MetaLab: Few-Shot Game Changer for Image Recognitioncited by 0
  4. 2025Color as the Impetus: Transforming Few-Shot Learnercited by 0
  5. 2025Cross-Domain Few-Shot Learning via Multi-View Collaborative Optimization with Vision-Language Modelscited by 0
  6. 2025A Domain-Adapted Lightweight Ensemble for Resource-Efficient Few-Shot Plant Disease Classificationcited by 0
  7. 2026Adapting Actively on the Fly: Relevance-Guided Online Meta-Learning with Latent Concepts for Geospatial Discoverycited by 0
  8. 2026Meta-Learning and Meta-Reinforcement Learning -- Tracing the Path towards DeepMind's Adaptive Agentcited by 0
  9. 2026From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoningcited by 0
  10. 2026Adaptive Learning Strategies for AoA-Based Outdoor Localization: A Comprehensive Frameworkcited by 0
  11. 2026Systematic Literature Review of Machine Learning Models and Applications for Text Recognitioncited by 0
  12. 2026A Data-Driven Multimodal Method for Early Detection of Coordinated Abnormal Behaviors in Live-Streaming Platformscited by 0
  13. 2026Are We Really Doing Few-Shot Learning? A Critical Examination of Pre-Training Assumptionscited by 0