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 8 of 18

351. ICML 2025Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
352. ICML 2025Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation
353. ICML 2025SLiM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression
354. ICML 2025The Missing Alignment Link of In-context Learning on Sequences
355. ICML 2025The Surprising Effectiveness of Test-Time Training for Few-Shot Learning
356. ICML 2025Unlocking the Power of SAM 2 for Few-Shot Segmentation
357. ICML 2025Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer
358. ICML 2025Zero-Shot Offline Imitation Learning via Optimal Transport
359. NeurIPS 2025A Few Moments Please: Scalable Graphon Learning via Moment Matching
360. NeurIPS 2025An Effective Levelling Paradigm for Unlabeled Scenarios
361. NeurIPS 2025Attack via Overfitting: 10-shot Benign Fine-tuning to Jailbreak LLMs
362. NeurIPS 2025Blackbox Model Provenance via Palimpsestic Membership Inference
363. NeurIPS 2025Dataset Distillation for Pre-Trained Self-Supervised Vision Models
364. NeurIPS 2025DETree: DEtecting Human-AI Collaborative Texts via Tree-Structured Hierarchical Representation Learning
365. NeurIPS 2025Diffusion-Classifier Synergy: Reward-Aligned Learning via Mutual Boosting Loop for FSCIL
366. NeurIPS 2025Domain-Specific Pruning of Large Mixture-of-Experts Models with Few-shot Demonstrations
367. NeurIPS 2025DON’T NEED RETRAINING: A Mixture of DETR and Vision Foundation Models for Cross-Domain Few-Shot Object Detection
368. NeurIPS 2025Dual Alignment Framework for Few-shot Learning with Inter-Set and Intra-Set Shifts
369. NeurIPS 2025Enhancing Zero-Shot Black-Box Optimization via Pretrained Models with Efficient Population Modeling, Interaction, and Stable Gradient Approximation
370. NeurIPS 2025Evolving and Regularizing Meta-Environment Learner for Fine-Grained Few-Shot Class-Incremental Learning
371. NeurIPS 2025Fast exact recovery of noisy matrix from few entries: the infinity norm approach
372. NeurIPS 2025Few-Shot Knowledge Distillation of LLMs With Counterfactual Explanations
373. NeurIPS 2025Few-Shot Learning from Gigapixel Images via Hierarchical Vision-Language Alignment and Modeling
374. NeurIPS 2025FSEO: Few-Shot Evolutionary Optimization via Meta-Learning for Expensive Multi-Objective Optimization
375. NeurIPS 2025Global Prompt Refinement with Non-Interfering Attention Masking for One-Shot Federated Learning
376. NeurIPS 2025GLVD: Guided Learned Vertex Descent
377. NeurIPS 2025Graph Few-Shot Learning via Adaptive Spectrum Experts and Cross-Set Distribution Calibration
378. NeurIPS 2025Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning
379. NeurIPS 2025Improving Diffusion-based Inverse Algorithms under Few-Step Constraint via Linear Extrapolation
380. NeurIPS 2025InvFusion: Bridging Supervised and Zero-shot Diffusion for Inverse Problems
381. NeurIPS 2025L2DGCN: Learnable Enhancement and Label Selection Dynamic Graph Convolutional Networks for Mitigating Degree Bias
382. NeurIPS 2025Learning to Learn with Contrastive Meta-Objective
383. NeurIPS 2025Learning to Rank for In-Context Example Retrieval
384. NeurIPS 2025MAPLE: Multi-scale Attribute-enhanced Prompt Learning for Few-shot Whole Slide Image Classification
385. NeurIPS 2025Meta-Learning an In-Context Transformer Model of Human Higher Visual Cortex
386. NeurIPS 2025MoEMeta: Mixture-of-Experts Meta Learning for Few-Shot Relational Learning
387. NeurIPS 2025MonarchAttention: Zero-Shot Conversion to Fast, Hardware-Aware Structured Attention
388. NeurIPS 2025Multi-Modal Interactive Agent Layer for Few-Shot Universal Cross-Domain Retrieval and Beyond
389. NeurIPS 2025Multi-Objective One-Shot Pruning for Large Language Models
390. NeurIPS 2025Noise Matters: Optimizing Matching Noise for Diffusion Classifiers
391. NeurIPS 2025NormFit: A Lightweight Solution for Few-Shot Federated Learning with Non-IID Data
392. NeurIPS 2025Novel View Synthesis from A Few Glimpses via Test-Time Natural Video Completion
393. NeurIPS 2025One Prompt Fits All: Universal Graph Adaptation for Pretrained Models
394. NeurIPS 2025Optimization Inspired Few-Shot Adaptation for Large Language Models
395. NeurIPS 2025Parameter-Free Hypergraph Neural Network for Few-Shot Node Classification
396. NeurIPS 2025PLANA3R: Zero-shot Metric Planar 3D Reconstruction via Feed-forward Planar Splatting
397. NeurIPS 2025Precise Diffusion Inversion: Towards Novel Samples and Few-Step Models
398. NeurIPS 2025Preference-driven Knowledge Distillation for Few-shot Node Classification
399. NeurIPS 2025Reasoning Beyond Points: A Visual Introspective Approach for Few-Shot 3D Segmentation
400. NeurIPS 2025ReDi: Rectified Discrete Flow

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.