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 5 of 6

201. NeurIPS 2023Extensible Prompts for Language Models on Zero-shot Language Style Customization
202. NeurIPS 2023Fairness-guided Few-shot Prompting for Large Language Models
203. NeurIPS 2023FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning
204. NeurIPS 2023FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning
205. NeurIPS 2023Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration
206. NeurIPS 2023Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory
207. NeurIPS 2023Focus on Query: Adversarial Mining Transformer for Few-Shot Segmentation
208. NeurIPS 2023Focus Your Attention when Few-Shot Classification
209. NeurIPS 2023Generalizable One-shot 3D Neural Head Avatar
210. NeurIPS 2023Geodesic Multi-Modal Mixup for Robust Fine-Tuning
211. NeurIPS 2023GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning
212. NeurIPS 2023GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection
213. NeurIPS 2023Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning
214. NeurIPS 2023How Re-sampling Helps for Long-Tail Learning?
215. NeurIPS 2023Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language
216. NeurIPS 2023Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach
217. NeurIPS 2023Hyperbolic Space with Hierarchical Margin Boosts Fine-Grained Learning from Coarse Labels
218. NeurIPS 2023Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data
219. NeurIPS 2023Improving neural network representations using human similarity judgments
220. NeurIPS 2023Interactive Visual Reasoning under Uncertainty
221. NeurIPS 2023Intra-Modal Proxy Learning for Zero-Shot Visual Categorization with CLIP
222. NeurIPS 2023Learning DAGs from Data with Few Root Causes
223. NeurIPS 2023Learning Functional Transduction
224. NeurIPS 2023Learning Large-scale Neural Fields via Context Pruned Meta-Learning
225. NeurIPS 2023Learning Mask-aware CLIP Representations for Zero-Shot Segmentation
226. NeurIPS 2023LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning
227. NeurIPS 2023Low-shot Object Learning with Mutual Exclusivity Bias
228. NeurIPS 2023Meta-AdaM: An Meta-Learned Adaptive Optimizer with Momentum for Few-Shot Learning
229. NeurIPS 2023Meta-Adapter: An Online Few-shot Learner for Vision-Language Model
230. NeurIPS 2023Meta-in-context learning in large language models
231. NeurIPS 2023Meta-Learning with Neural Bandit Scheduler
232. NeurIPS 2023MGDD: A Meta Generator for Fast Dataset Distillation
233. NeurIPS 2023Mitigating the Effect of Incidental Correlations on Part-based Learning
234. NeurIPS 2023Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder
235. NeurIPS 2023One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning
236. NeurIPS 2023Online Constrained Meta-Learning: Provable Guarantees for Generalization
237. NeurIPS 2023Optimistic Meta-Gradients
238. NeurIPS 2023PAPR: Proximity Attention Point Rendering
239. NeurIPS 2023Parameterizing Context: Unleashing the Power of Parameter-Efficient Fine-Tuning and In-Context Tuning for Continual Table Semantic Parsing
240. NeurIPS 2023ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion
241. NeurIPS 2023Prototypical Variational Autoencoder for 3D Few-shot Object Detection
242. NeurIPS 2023Read and Reap the Rewards: Learning to Play Atari with the Help of Instruction Manuals
243. NeurIPS 2023Recurrent Hypernetworks are Surprisingly Strong in Meta-RL
244. NeurIPS 2023Regularity as Intrinsic Reward for Free Play
245. NeurIPS 2023Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification
246. NeurIPS 2023S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions
247. NeurIPS 2023Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction
248. NeurIPS 2023SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning
249. NeurIPS 2023TexQ: Zero-shot Network Quantization with Texture Feature Distribution Calibration
250. NeurIPS 2023The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification

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.