Few-Shot Learning papers, 2023–2026

Key findings

• Few-Shot Learning fell from 251 papers in 2023 to 224 in 2026, so interest is cooling.
• CVPR publishes the most Few-Shot Learning work: 303 papers from 2023 to 2026, 34% of the four-venue total.
• The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 4 in 2023 to 24 in 2026.
• Among the 5 topics under Meta-Learning and Transfer, it ranks #4 by 2026 paper count; the fastest grower in the group, Foundation Model Adaptation, is up 3.8x versus 0.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026BAPM: Boundary-Aware Prompt Mining for Training-Free Few-Shot Medical Image Segmentation
• ICML 2026Bayes-inspired Integration of Pretrained Priors and Few-Shot Evidence for Few-Shot Classification
• ICLR 2026Adaptive Concept Discovery for Interpretable Few-Shot Text Classification
• CVPR 2026A Closer Look at Cross-Domain Few-Shot Object Detection Fine-Tuning Matters
• NeurIPS 2025A Few Moments Please: Scalable Graphon Learning via Moment Matching
• ICML 2025FedBEns: One-Shot Federated Learning based on Bayesian Ensemble
• ICLR 2025Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint
• CVPR 20253D Prior Is All You Need: Cross-Task Few-shot 2D Gaze Estimation
• NeurIPS 2024Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark
• ICML 2024Accelerating Convergence in Bayesian Few-Shot Classification
• ICLR 2024Few-shot Hybrid Domain Adaptation of Image Generator
• CVPR 2024Deformable One-shot Face Stylization via DINO Semantic Guidance
• NeurIPS 2023Alignment with human representations supports robust few-shot learning
• ICML 2023A Category-theoretical Meta-analysis of Definitions of Disentanglement
• ICLR 2023Bidirectional Language Models Are Also Few-shot Learners
• CVPR 2023A Meta-Learning Approach to Predicting Performance and Data Requirements
• NeurIPS 2026Beyond Normal References: Discriminative Few-Shot Anomaly Detection
• ICML 2026BiCrossNet with Decoupled Dual Generators: A Parameter‑Efficient and Generalizable Few‑Shot Custom Gesture Recognition Framework
• ICLR 2026Dual Distillation for Few-Shot Anomaly Detection
• CVPR 2026Beyond Patches Global-aware Autoregressive Model for Multimodal Few-Shot Font Generation

All Few-Shot Learning papers

76 papers, page 1 of 2

1. NeurIPS 2023A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm
2. NeurIPS 2023A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence
3. NeurIPS 2023Alignment with human representations supports robust few-shot learning
4. NeurIPS 2023An Efficient Dataset Condensation Plugin and Its Application to Continual Learning
5. NeurIPS 2023Context Shift Reduction for Offline Meta-Reinforcement Learning
6. NeurIPS 2023Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes
7. NeurIPS 2023Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL
8. NeurIPS 2023CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion
9. NeurIPS 2023DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation
10. NeurIPS 2023Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks
11. NeurIPS 2023DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation
12. NeurIPS 2023Domain Re-Modulation for Few-Shot Generative Domain Adaptation
13. NeurIPS 2023EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
14. NeurIPS 2023Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
15. NeurIPS 2023Explore to Generalize in Zero-Shot RL
16. NeurIPS 2023Exploring Diverse In-Context Configurations for Image Captioning
17. NeurIPS 2023ExPT: Synthetic Pretraining for Few-Shot Experimental Design
18. NeurIPS 2023Extensible Prompts for Language Models on Zero-shot Language Style Customization
19. NeurIPS 2023Fairness-guided Few-shot Prompting for Large Language Models
20. NeurIPS 2023FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning
21. NeurIPS 2023FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning
22. NeurIPS 2023Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration
23. NeurIPS 2023Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory
24. NeurIPS 2023Focus on Query: Adversarial Mining Transformer for Few-Shot Segmentation
25. NeurIPS 2023Focus Your Attention when Few-Shot Classification
26. NeurIPS 2023Generalizable One-shot 3D Neural Head Avatar
27. NeurIPS 2023Geodesic Multi-Modal Mixup for Robust Fine-Tuning
28. NeurIPS 2023GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning
29. NeurIPS 2023GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection
30. NeurIPS 2023Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning
31. NeurIPS 2023How Re-sampling Helps for Long-Tail Learning?
32. NeurIPS 2023Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language
33. NeurIPS 2023Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach
34. NeurIPS 2023Hyperbolic Space with Hierarchical Margin Boosts Fine-Grained Learning from Coarse Labels
35. NeurIPS 2023Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data
36. NeurIPS 2023Improving neural network representations using human similarity judgments
37. NeurIPS 2023Interactive Visual Reasoning under Uncertainty
38. NeurIPS 2023Intra-Modal Proxy Learning for Zero-Shot Visual Categorization with CLIP
39. NeurIPS 2023Learning DAGs from Data with Few Root Causes
40. NeurIPS 2023Learning Functional Transduction
41. NeurIPS 2023Learning Large-scale Neural Fields via Context Pruned Meta-Learning
42. NeurIPS 2023Learning Mask-aware CLIP Representations for Zero-Shot Segmentation
43. NeurIPS 2023LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning
44. NeurIPS 2023Low-shot Object Learning with Mutual Exclusivity Bias
45. NeurIPS 2023Meta-AdaM: An Meta-Learned Adaptive Optimizer with Momentum for Few-Shot Learning
46. NeurIPS 2023Meta-Adapter: An Online Few-shot Learner for Vision-Language Model
47. NeurIPS 2023Meta-in-context learning in large language models
48. NeurIPS 2023Meta-Learning with Neural Bandit Scheduler
49. NeurIPS 2023MGDD: A Meta Generator for Fast Dataset Distillation
50. NeurIPS 2023Mitigating the Effect of Incidental Correlations on Part-based Learning

FAQ

How many Few-Shot Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

898 in total: 251 in 2023, 220 in 2024, 203 in 2025, 224 in 2026.

How many Few-Shot Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 51 Few-Shot Learning papers, versus 68 the year before.

How many Few-Shot Learning papers are at ICLR 2026?

ICLR 2026 has 38 Few-Shot Learning papers, versus 36 the year before.

How many Few-Shot Learning papers are at ICML 2026?

ICML 2026 has 56 Few-Shot Learning papers, versus 35 the year before.

How many Few-Shot Learning papers are at CVPR 2026?

CVPR 2026 has 79 Few-Shot Learning papers, versus 64 the year before.

Which conference publishes the most Few-Shot Learning papers?

CVPR, with 303 papers from 2023 to 2026.