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

68 papers, page 1 of 2

1. NeurIPS 2025A Few Moments Please: Scalable Graphon Learning via Moment Matching
2. NeurIPS 2025An Effective Levelling Paradigm for Unlabeled Scenarios
3. NeurIPS 2025Attack via Overfitting: 10-shot Benign Fine-tuning to Jailbreak LLMs
4. NeurIPS 2025Blackbox Model Provenance via Palimpsestic Membership Inference
5. NeurIPS 2025Dataset Distillation for Pre-Trained Self-Supervised Vision Models
6. NeurIPS 2025DETree: DEtecting Human-AI Collaborative Texts via Tree-Structured Hierarchical Representation Learning
7. NeurIPS 2025Diffusion-Classifier Synergy: Reward-Aligned Learning via Mutual Boosting Loop for FSCIL
8. NeurIPS 2025Domain-Specific Pruning of Large Mixture-of-Experts Models with Few-shot Demonstrations
9. NeurIPS 2025DON’T NEED RETRAINING: A Mixture of DETR and Vision Foundation Models for Cross-Domain Few-Shot Object Detection
10. NeurIPS 2025Dual Alignment Framework for Few-shot Learning with Inter-Set and Intra-Set Shifts
11. NeurIPS 2025Enhancing Zero-Shot Black-Box Optimization via Pretrained Models with Efficient Population Modeling, Interaction, and Stable Gradient Approximation
12. NeurIPS 2025Evolving and Regularizing Meta-Environment Learner for Fine-Grained Few-Shot Class-Incremental Learning
13. NeurIPS 2025Fast exact recovery of noisy matrix from few entries: the infinity norm approach
14. NeurIPS 2025Few-Shot Knowledge Distillation of LLMs With Counterfactual Explanations
15. NeurIPS 2025Few-Shot Learning from Gigapixel Images via Hierarchical Vision-Language Alignment and Modeling
16. NeurIPS 2025FSEO: Few-Shot Evolutionary Optimization via Meta-Learning for Expensive Multi-Objective Optimization
17. NeurIPS 2025Global Prompt Refinement with Non-Interfering Attention Masking for One-Shot Federated Learning
18. NeurIPS 2025GLVD: Guided Learned Vertex Descent
19. NeurIPS 2025Graph Few-Shot Learning via Adaptive Spectrum Experts and Cross-Set Distribution Calibration
20. NeurIPS 2025Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning
21. NeurIPS 2025Improving Diffusion-based Inverse Algorithms under Few-Step Constraint via Linear Extrapolation
22. NeurIPS 2025InvFusion: Bridging Supervised and Zero-shot Diffusion for Inverse Problems
23. NeurIPS 2025L2DGCN: Learnable Enhancement and Label Selection Dynamic Graph Convolutional Networks for Mitigating Degree Bias
24. NeurIPS 2025Learning to Learn with Contrastive Meta-Objective
25. NeurIPS 2025Learning to Rank for In-Context Example Retrieval
26. NeurIPS 2025MAPLE: Multi-scale Attribute-enhanced Prompt Learning for Few-shot Whole Slide Image Classification
27. NeurIPS 2025Meta-Learning an In-Context Transformer Model of Human Higher Visual Cortex
28. NeurIPS 2025MoEMeta: Mixture-of-Experts Meta Learning for Few-Shot Relational Learning
29. NeurIPS 2025MonarchAttention: Zero-Shot Conversion to Fast, Hardware-Aware Structured Attention
30. NeurIPS 2025Multi-Modal Interactive Agent Layer for Few-Shot Universal Cross-Domain Retrieval and Beyond
31. NeurIPS 2025Multi-Objective One-Shot Pruning for Large Language Models
32. NeurIPS 2025Noise Matters: Optimizing Matching Noise for Diffusion Classifiers
33. NeurIPS 2025NormFit: A Lightweight Solution for Few-Shot Federated Learning with Non-IID Data
34. NeurIPS 2025Novel View Synthesis from A Few Glimpses via Test-Time Natural Video Completion
35. NeurIPS 2025One Prompt Fits All: Universal Graph Adaptation for Pretrained Models
36. NeurIPS 2025Optimization Inspired Few-Shot Adaptation for Large Language Models
37. NeurIPS 2025Parameter-Free Hypergraph Neural Network for Few-Shot Node Classification
38. NeurIPS 2025PLANA3R: Zero-shot Metric Planar 3D Reconstruction via Feed-forward Planar Splatting
39. NeurIPS 2025Precise Diffusion Inversion: Towards Novel Samples and Few-Step Models
40. NeurIPS 2025Preference-driven Knowledge Distillation for Few-shot Node Classification
41. NeurIPS 2025Reasoning Beyond Points: A Visual Introspective Approach for Few-Shot 3D Segmentation
42. NeurIPS 2025ReDi: Rectified Discrete Flow
43. NeurIPS 2025ReinAD: Towards Real-world Industrial Anomaly Detection with a Comprehensive Contrastive Dataset
44. NeurIPS 2025Reinforcement learning for one-shot DAG scheduling with comparability identification and dense reward
45. NeurIPS 2025Repurposing Marigold for Zero-Shot Metric Depth Estimation via Defocus Blur Cues
46. NeurIPS 2025SANSA: Unleashing the Hidden Semantics in SAM2 for Few-Shot Segmentation
47. NeurIPS 2025SegGraph: Leveraging Graphs of SAM Segments for Few-Shot 3D Part Segmentation
48. NeurIPS 2025Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
49. NeurIPS 2025Shortcutting Pre-trained Flow Matching Diffusion Models is Almost Free Lunch
50. NeurIPS 2025Support Vector Generation: Kernelizing Large Language Models for Efficient Zero‑Shot NLP

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.