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

168 papers, page 3 of 4

101. ICML 2024DMTG: One-Shot Differentiable Multi-Task Grouping
102. ICML 2024Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods
103. ICML 2024Enabling Few-Shot Learning with PID Control: A Layer Adaptive Optimizer
104. ICML 2024Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings
105. ICML 2024Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind
106. ICML 2024Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries
107. ICML 2024Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations
108. ICML 2024Hyperbolic Optimizer as a Dynamical System
109. ICML 2024Implicit meta-learning may lead language models to trust more reliable sources
110. ICML 2024In-Context Unlearning: Language Models as Few-Shot Unlearners
111. ICML 2024Language-Driven Cross-Modal Classifier for Zero-Shot Multi-Label Image Recognition
112. ICML 2024Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning
113. ICML 2024Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition
114. ICML 2024Learning Multiple Secrets in Mastermind
115. ICML 2024Learning to Route Among Specialized Experts for Zero-Shot Generalization
116. ICML 2024MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent
117. ICML 2024Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games
118. ICML 2024MD tree: a model-diagnostic tree grown on loss landscape
119. ICML 2024Meta Evidential Transformer for Few-Shot Open-Set Recognition
120. ICML 2024MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence
121. ICML 2024More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
122. ICML 2024One Meta-tuned Transformer is What You Need for Few-shot Learning
123. ICML 2024One-Shot Strategic Classification Under Unknown Costs
124. ICML 2024PID: Prompt-Independent Data Protection Against Latent Diffusion Models
125. ICML 2024Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss
126. ICML 2024The Balanced-Pairwise-Affinities Feature Transform
127. ICML 2024Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts
128. ICML 2024Zero-Shot Reinforcement Learning via Function Encoders
129. ICML 2023A Category-theoretical Meta-analysis of Definitions of Disentanglement
130. ICML 2023A Closer Look at Few-shot Classification Again
131. ICML 2023Abstract-to-Executable Trajectory Translation for One-Shot Task Generalization
132. ICML 2023Adaptive Compositional Continual Meta-Learning
133. ICML 2023Adaptive IMLE for Few-shot Pretraining-free Generative Modelling
134. ICML 2023Benign Overfitting in Two-layer ReLU Convolutional Neural Networks
135. ICML 2023CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets
136. ICML 2023Cooperative Open-ended Learning Framework for Zero-Shot Coordination
137. ICML 2023Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation
138. ICML 2023Does Continual Learning Equally Forget All Parameters?
139. ICML 2023Effective Structured Prompting by Meta-Learning and Representative Verbalizer
140. ICML 2023Efficient Training of Language Models using Few-Shot Learning
141. ICML 2023Evolving Semantic Prototype Improves Generative Zero-Shot Learning
142. ICML 2023Few-bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction
143. ICML 2023Few-Sample Feature Selection via Feature Manifold Learning
144. ICML 2023GeCoNeRF: Few-shot Neural Radiance Fields via Geometric Consistency
145. ICML 2023HyperTuning: Toward Adapting Large Language Models without Back-propagation
146. ICML 2023Interval Bound Interpolation for Few-shot Learning with Few Tasks
147. ICML 2023Learning the Dynamics of Sparsely Observed Interacting Systems
148. ICML 2023Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
149. ICML 2023Lifelong Language Pretraining with Distribution-Specialized Experts
150. ICML 2023Meta Optimal Transport

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.