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

251 papers, page 4 of 6

151. ICML 2023GeCoNeRF: Few-shot Neural Radiance Fields via Geometric Consistency
152. ICML 2023HyperTuning: Toward Adapting Large Language Models without Back-propagation
153. ICML 2023Interval Bound Interpolation for Few-shot Learning with Few Tasks
154. ICML 2023Learning the Dynamics of Sparsely Observed Interacting Systems
155. ICML 2023Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
156. ICML 2023Lifelong Language Pretraining with Distribution-Specialized Experts
157. ICML 2023Meta Optimal Transport
158. ICML 2023Meta-learning Parameterized Skills
159. ICML 2023Meta-Learning the Inductive Bias of Simple Neural Circuits
160. ICML 2023MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks
161. ICML 2023MEWL: Few-shot multimodal word learning with referential uncertainty
162. ICML 2023Model-agnostic Measure of Generalization Difficulty
163. ICML 2023One-Shot Federated Conformal Prediction
164. ICML 2023One-shot Imitation in a Non-Stationary Environment via Multi-Modal Skill
165. ICML 2023Online Prototype Alignment for Few-shot Policy Transfer
166. ICML 2023PreNAS: Preferred One-Shot Learning Towards Efficient Neural Architecture Search
167. ICML 2023Reward-Mixing MDPs with Few Latent Contexts are Learnable
168. ICML 2023SemSup-XC: Semantic Supervision for Zero and Few-shot Extreme Classification
169. ICML 2023Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning
170. ICML 2023SparseGPT: Massive Language Models Can be Accurately Pruned in One-Shot
171. ICML 2023The Unreasonable Effectiveness of Few-shot Learning for Machine Translation
172. ICML 2023Towards Controlled Data Augmentations for Active Learning
173. ICML 2023Tuning Language Models as Training Data Generators for Augmentation-Enhanced Few-Shot Learning
174. ICML 2023Uncertainty Estimation by Fisher Information-based Evidential Deep Learning
175. ICML 2023Variance Control for Distributional Reinforcement Learning
176. NeurIPS 2023A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm
177. NeurIPS 2023A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence
178. NeurIPS 2023Alignment with human representations supports robust few-shot learning
179. NeurIPS 2023An Efficient Dataset Condensation Plugin and Its Application to Continual Learning
180. NeurIPS 2023Context Shift Reduction for Offline Meta-Reinforcement Learning
181. NeurIPS 2023Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes
182. NeurIPS 2023Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL
183. NeurIPS 2023CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion
184. NeurIPS 2023DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation
185. NeurIPS 2023Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks
186. NeurIPS 2023DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation
187. NeurIPS 2023Domain Re-Modulation for Few-Shot Generative Domain Adaptation
188. NeurIPS 2023EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
189. NeurIPS 2023Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
190. NeurIPS 2023Explore to Generalize in Zero-Shot RL
191. NeurIPS 2023Exploring Diverse In-Context Configurations for Image Captioning
192. NeurIPS 2023ExPT: Synthetic Pretraining for Few-Shot Experimental Design
193. NeurIPS 2023Extensible Prompts for Language Models on Zero-shot Language Style Customization
194. NeurIPS 2023Fairness-guided Few-shot Prompting for Large Language Models
195. NeurIPS 2023FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning
196. NeurIPS 2023FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning
197. NeurIPS 2023Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration
198. NeurIPS 2023Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory
199. NeurIPS 2023Focus on Query: Adversarial Mining Transformer for Few-Shot Segmentation
200. NeurIPS 2023Focus Your Attention when Few-Shot 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.