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 4 of 6

151. NeurIPS 2024Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses
152. NeurIPS 2024Kermut: Composite kernel regression for protein variant effects
153. NeurIPS 2024Knowledge Composition using Task Vectors with Learned Anisotropic Scaling
154. NeurIPS 2024Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation
155. NeurIPS 2024Limits of Transformer Language Models on Learning to Compose Algorithms
156. NeurIPS 2024Many-shot Jailbreaking
157. NeurIPS 2024Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control
158. NeurIPS 2024Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning
159. NeurIPS 2024Meta-Learning Universal Priors Using Non-Injective Change of Variables
160. NeurIPS 2024Mind the Gap Between Prototypes and Images in Cross-domain Finetuning
161. NeurIPS 2024Mixture of Adversarial LoRAs: Boosting Robust Generalization in Meta-Tuning
162. NeurIPS 2024Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning
163. NeurIPS 2024One-shot Federated Learning via Synthetic Distiller-Distillate Communication
164. NeurIPS 2024Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property Prediction
165. NeurIPS 2024Pretrained Optimization Model for Zero-Shot Black Box Optimization
166. NeurIPS 2024QueST: Self-Supervised Skill Abstractions for Learning Continuous Control
167. NeurIPS 2024Rapid Plug-in Defenders
168. NeurIPS 2024Revisiting Ensembling in One-Shot Federated Learning
169. NeurIPS 2024Robust Fine-tuning of Zero-shot Models via Variance Reduction
170. NeurIPS 2024Skill-aware Mutual Information Optimisation for Zero-shot Generalisation in Reinforcement Learning
171. NeurIPS 2024SpeAr: A Spectral Approach for Zero-Shot Node Classification
172. NeurIPS 2024Structure Consistent Gaussian Splatting with Matching Prior for Few-shot Novel View Synthesis
173. NeurIPS 2024The Representation Landscape of Few-Shot Learning and Fine-Tuning in Large Language Models
174. NeurIPS 2024Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning
175. NeurIPS 2024Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
176. NeurIPS 2024TransAgent: Transfer Vision-Language Foundation Models with Heterogeneous Agent Collaboration
177. NeurIPS 2024Transformers are Minimax Optimal Nonparametric In-Context Learners
178. NeurIPS 2024UniAudio 1.5: Large Language Model-Driven Audio Codec is A Few-Shot Audio Task Learner
179. NeurIPS 2024Unleashing the Potential of the Diffusion Model in Few-shot Semantic Segmentation
180. NeurIPS 2024XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
181. NeurIPS 2024Zero-Shot Scene Reconstruction from Single Images with Deep Prior Assembly
182. NeurIPS 2024Zero-Shot Tokenizer Transfer
183. NeurIPS 2024Zero-Shot Transfer of Neural ODEs
184. NeurIPS 2023A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm
185. NeurIPS 2023A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence
186. NeurIPS 2023Alignment with human representations supports robust few-shot learning
187. NeurIPS 2023An Efficient Dataset Condensation Plugin and Its Application to Continual Learning
188. NeurIPS 2023Context Shift Reduction for Offline Meta-Reinforcement Learning
189. NeurIPS 2023Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes
190. NeurIPS 2023Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL
191. NeurIPS 2023CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion
192. NeurIPS 2023DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation
193. NeurIPS 2023Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks
194. NeurIPS 2023DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation
195. NeurIPS 2023Domain Re-Modulation for Few-Shot Generative Domain Adaptation
196. NeurIPS 2023EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
197. NeurIPS 2023Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
198. NeurIPS 2023Explore to Generalize in Zero-Shot RL
199. NeurIPS 2023Exploring Diverse In-Context Configurations for Image Captioning
200. NeurIPS 2023ExPT: Synthetic Pretraining for Few-Shot Experimental Design

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.