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

259 papers, page 1 of 6

1. NeurIPS 2026AdaWM: Few-Shot Adaptation of World Models to Unseen Dynamical Regimes
2. NeurIPS 2026BAPM: Boundary-Aware Prompt Mining for Training-Free Few-Shot Medical Image Segmentation
3. NeurIPS 2026Beyond Normal References: Discriminative Few-Shot Anomaly Detection
4. NeurIPS 2026CausalCine: Real-Time Autoregressive Generation for Multi-Shot Video Narratives
5. NeurIPS 2026Classification Fields: Arbitrarily Fine Recursive Hierarchical Clustering From Few Examples
6. NeurIPS 2026Coresets for Clustering Using Noisy Comparisons and Few Distance Queries
7. NeurIPS 2026CORP: Closed-Form One-shot Representation-Preserving Structured Pruning for Transformers
8. NeurIPS 2026Direct Product Flow Matching: Decoupling Radial and Angular Dynamics for Few-Shot Adaptation
9. NeurIPS 2026EENAS: Zero-Shot Energy-Efficiency-Aware Neural Architecture Search
10. NeurIPS 2026Eliciting Zero-Shot Named Entity Recognition in Large Language Models via Instruction Semantic Elaboration
11. NeurIPS 2026EpistasisBench: Revealing Structural Limitations of Zero-Shot Protein Language Models
12. NeurIPS 2026Few-shot Task Learning via Compositional Concept Inference
13. NeurIPS 2026Few-Shot Truly Benign DPO Attack for Jailbreaking LLMs
14. NeurIPS 2026Few-Step Cofolding with All-Atom Flow Maps
15. NeurIPS 2026Few-Step Diffusion Language Models via Trajectory Self-Distillation
16. NeurIPS 2026Full Fine-Tuning Is Not the Problem: Why Adam Fails and SGD Succeeds in Few-Shot CLIP Adaptation
17. NeurIPS 2026GADMVP: Adaptive Few-Shot Graph-Level Anomaly Detection with Multi-View Structured Prompting
18. NeurIPS 2026GATE-AD: Graph Attention Network Encoding for Few-Shot Industrial Visual Anomaly Detection
19. NeurIPS 2026GCD: GCM-consistent Diffusion for Zero-shot Downscaling across Heterogeneous GCMs
20. NeurIPS 2026Geometry over Density: Few-Shot Cross-Domain OOD Detection
21. NeurIPS 2026Hyperspherical Local Margin Retraction for Zero-Shot Instance-Wise Machine Unlearning
22. NeurIPS 2026Large-Scale Pretraining unlocks Few-Shot Prediction for Relational Data
23. NeurIPS 2026Learning Transferable Cross-Day Representations for Few-Shot Neural Decoding
24. NeurIPS 2026Listening to the Wise Few: Query–Key Alignment Unlocks Latent Correct Answers in Large Language Models
25. NeurIPS 2026Matching-Based Few-Shot Semantic Segmentation Models Are Interpretable by Design
26. NeurIPS 2026Matching2Matching: Zero-Shot Light Field Image Denoising with Matching View Construction
27. NeurIPS 2026Meta-Reinforcement Learning with Zero-Shot Reinforcement Learning
28. NeurIPS 2026One-Shot Federated Graph Learning via High-Fidelity Proxies and Transferability-Guided Collaboration
29. NeurIPS 2026One-Shot Private Confidence Regions via Resampling
30. NeurIPS 2026ONE-SHOT: Compositional Human-Environment Video Synthesis via Spatial-Decoupled Motion Injection and Hybrid Context Integration
31. NeurIPS 2026PRIM: Meta-Learned Bayesian Root Cause Analysis
32. NeurIPS 2026RAPTOR: Ridge-Adaptive Logistic Probes
33. NeurIPS 2026Roll2Depth: Zero-Shot Metric Depth Estimation Exploiting Camera's Rolling Shutter Effect
34. NeurIPS 2026ScreenShot: A Foundation Model for Few-Shot Combination Drug Screening
35. NeurIPS 2026SD-LoRA: Training-Time Structural Distillation into LoRA for Few-Shot Vision-Language Adaptation
36. NeurIPS 2026Seeking the Unfamiliar but Memorable: Conceptual Creativity as Meta-Learning
37. NeurIPS 2026Semantic-Statistical Prior Banks for Federated Low-Shot Learning under Non-IID Clients
38. NeurIPS 2026Shepherd: A Runtime Substrate Empowering Meta-Agents with a Formalized Execution Trace
39. NeurIPS 2026Stabilizing Few-Shot Object Detection with Language-Conditioned Probabilistic Prototypes
40. NeurIPS 2026Temporal Consistency Improves Generalization in Contextual Offline Meta Reinforcement Learning
41. NeurIPS 2026The Laplacian Keyboard: Beyond the Linear Span
42. NeurIPS 2026Trajectory as the Teacher: Few-Step Discrete Flow Matching via Energy-Navigated Distillation
43. NeurIPS 2026Transcoda: End-to-End Zero-Shot Optical Music Recognition via Data-Centric Synthetic Training
44. NeurIPS 2026Ultra Fast PDE Solving via Physics Guided Few-step Diffusion
45. NeurIPS 2026Umbilic Multinomial Logistic Regression
46. NeurIPS 2026Unlocking Compositional Generalization in Continual Few-Shot Learning
47. NeurIPS 2026VIGOR: Zero-Shot Visual Generalization via Latent-Space Consistency in Model-Based Reinforcement Learning
48. NeurIPS 2026What Fits (Into Few Tokens) Doesn't Overfit: Compression and Generalization in ML Research Agents
49. NeurIPS 2026When Does Subspace Direction Matter for LoRA? Regime Analysis of the Magnitude Principle in Few-Shot Adaptation
50. NeurIPS 2026Zero-Shot Coordination among LLM Agents

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.