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

897 papers, page 4 of 18

151. ICML 2026Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning
152. ICML 2026Path-Decoupled Hyperbolic Flow Matching for Few-Shot Adaptation
153. ICML 2026Prompt Tuning for CLIP on the Pretrained Manifold
154. ICML 2026Rank-guided Diffusion for Noise Few-Shot Learning
155. ICML 2026Reasoning Can Be Restored by Correcting a Few Decision Tokens
156. ICML 2026ReAugment: Targeted Few-Shot Time Series Augmentation via Model Zoo-Guided Reinforcement Learning
157. ICML 2026ReCoG: Relational and Compact Context Graph Learning for Few-shot Molecular Property Prediction
158. ICML 2026Remove the Ambiguity: Few-shot Multimodal Anomaly Detection Using Crossmodal Feature Replacers
159. ICML 2026SEMIR: Semantic Minor-Induced Representation Learning on Graphs for Visual Segmentation
160. ICML 2026SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot
161. ICML 2026Structure-Centric Graph Foundation Model via Geometric Bases
162. ICML 2026Structured Expert Routing with Multi-View Task Priors for Offline Meta-Reinforcement Learning
163. ICML 2026The Hippocampal Place Field Gradient: A Bio-inspired Framework Building Multiscale Representation for Better Sample Efficiency
164. ICML 2026Theoretical Guarantees for One-Shot Magnitude Pruning and Compute-Adaptive Early Exit
165. ICML 2026Tiny Brains, Giant Impact: Uncovering the Keystone Neurons of LLM with Just a Few Prompts
166. ICML 2026Towards a Unified Generative Model for Scarce Time Series with Domain Experts
167. ICML 2026Universal Algorithm-Implicit Learning
168. ICML 2026Unsupervised Process-Aware Coreset Selection for In-Context Learning
169. ICML 2026URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization
170. ICML 2026Weight-Space Learning for Certifiable Few-shot Transfer Learning
171. ICML 2026XTransfer: Modality-Agnostic Few-Shot Model Transfer for Human Sensing at the Edge
172. ICML 2026ZeroUnlearn: Few-Shot Knowledge Unlearning in Large Language Models
173. NeurIPS 2026AdaWM: Few-Shot Adaptation of World Models to Unseen Dynamical Regimes
174. NeurIPS 2026BAPM: Boundary-Aware Prompt Mining for Training-Free Few-Shot Medical Image Segmentation
175. NeurIPS 2026Beyond Normal References: Discriminative Few-Shot Anomaly Detection
176. NeurIPS 2026CausalCine: Real-Time Autoregressive Generation for Multi-Shot Video Narratives
177. NeurIPS 2026Classification Fields: Arbitrarily Fine Recursive Hierarchical Clustering From Few Examples
178. NeurIPS 2026Coresets for Clustering Using Noisy Comparisons and Few Distance Queries
179. NeurIPS 2026CORP: Closed-Form One-shot Representation-Preserving Structured Pruning for Transformers
180. NeurIPS 2026Direct Product Flow Matching: Decoupling Radial and Angular Dynamics for Few-Shot Adaptation
181. NeurIPS 2026EENAS: Zero-Shot Energy-Efficiency-Aware Neural Architecture Search
182. NeurIPS 2026Eliciting Zero-Shot Named Entity Recognition in Large Language Models via Instruction Semantic Elaboration
183. NeurIPS 2026EpistasisBench: Revealing Structural Limitations of Zero-Shot Protein Language Models
184. NeurIPS 2026Few-shot Task Learning via Compositional Concept Inference
185. NeurIPS 2026Few-Shot Truly Benign DPO Attack for Jailbreaking LLMs
186. NeurIPS 2026Few-Step Cofolding with All-Atom Flow Maps
187. NeurIPS 2026Few-Step Diffusion Language Models via Trajectory Self-Distillation
188. NeurIPS 2026Full Fine-Tuning Is Not the Problem: Why Adam Fails and SGD Succeeds in Few-Shot CLIP Adaptation
189. NeurIPS 2026GADMVP: Adaptive Few-Shot Graph-Level Anomaly Detection with Multi-View Structured Prompting
190. NeurIPS 2026GATE-AD: Graph Attention Network Encoding for Few-Shot Industrial Visual Anomaly Detection
191. NeurIPS 2026GCD: GCM-consistent Diffusion for Zero-shot Downscaling across Heterogeneous GCMs
192. NeurIPS 2026Geometry over Density: Few-Shot Cross-Domain OOD Detection
193. NeurIPS 2026Hyperspherical Local Margin Retraction for Zero-Shot Instance-Wise Machine Unlearning
194. NeurIPS 2026Large-Scale Pretraining unlocks Few-Shot Prediction for Relational Data
195. NeurIPS 2026Learning Transferable Cross-Day Representations for Few-Shot Neural Decoding
196. NeurIPS 2026Listening to the Wise Few: Query–Key Alignment Unlocks Latent Correct Answers in Large Language Models
197. NeurIPS 2026Matching-Based Few-Shot Semantic Segmentation Models Are Interpretable by Design
198. NeurIPS 2026Matching2Matching: Zero-Shot Light Field Image Denoising with Matching View Construction
199. NeurIPS 2026Meta-Reinforcement Learning with Zero-Shot Reinforcement Learning
200. NeurIPS 2026One-Shot Federated Graph Learning via High-Fidelity Proxies and Transferability-Guided Collaboration

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.