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 7 of 18

301. ICLR 2025Local-Prompt: Extensible Local Prompts for Few-Shot Out-of-Distribution Detection
302. ICLR 2025LOIRE: LifelOng learning on Incremental data via pre-trained language model gRowth Efficiently
303. ICLR 2025Making Text Embedders Few-Shot Learners
304. ICLR 2025Manifold Induced Biases for Zero-shot and Few-shot Detection of Generated Images
305. ICLR 2025Meta-Dynamical State Space Models for Integrative Neural Data Analysis
306. ICLR 2025Metalic: Meta-Learning In-Context with Protein Language Models
307. ICLR 2025Multi-Perspective Data Augmentation for Few-shot Object Detection
308. ICLR 2025Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation
309. ICLR 2025One-for-All Few-Shot Anomaly Detection via Instance-Induced Prompt Learning
310. ICLR 2025PEAR: Primitive Enabled Adaptive Relabeling for Boosting Hierarchical Reinforcement Learning
311. ICLR 2025Predicate Hierarchies Improve Few-Shot State Classification
312. ICLR 2025Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework
313. ICLR 2025Protein Language Model Fitness is a Matter of Preference
314. ICLR 2025Prototype antithesis for biological few-shot class-incremental learning
315. ICLR 2025Safety Alignment Should be Made More Than Just a Few Tokens Deep
316. ICLR 2025STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning
317. ICLR 2025SynQ: Accurate Zero-shot Quantization by Synthesis-aware Fine-tuning
318. ICLR 2025UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery
319. ICLR 2025Unsupervised Zero-Shot Reinforcement Learning via Dual-Value Forward-Backward Representation
320. ICLR 2025Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation
321. ICLR 2025Why In-Context Learning Models are Good Few-Shot Learners?
322. ICLR 2025Zero-Shot Natural Language Explanations
323. ICLR 2025ZeroDiff: Solidified Visual-semantic Correlation in Zero-Shot Learning
324. ICML 2025Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
325. ICML 2025Adaptive Multi-prompt Contrastive Network for Few-shot Out-of-distribution Detection
326. ICML 2025Alpha-SQL: Zero-Shot Text-to-SQL using Monte Carlo Tree Search
327. ICML 2025Bootstrapping Self-Improvement of Language Model Programs for Zero-Shot Schema Matching
328. ICML 2025CERTAIN: Context Uncertainty-aware One-Shot Adaptation for Context-based Offline Meta Reinforcement Learning
329. ICML 2025Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated Learning
330. ICML 2025DyPolySeg: Taylor Series-Inspired Dynamic Polynomial Fitting Network for Few-shot Point Cloud Semantic Segmentation
331. ICML 2025FedBEns: One-Shot Federated Learning based on Bayesian Ensemble
332. ICML 2025Federated Oriented Learning: A Practical One-Shot Personalized Federated Learning Framework
333. ICML 2025Feedforward Few-shot Species Range Estimation
334. ICML 2025Few-Shot Learner Generalizes Across AI-Generated Image Detection
335. ICML 2025FSTLLM: Spatio-Temporal LLM for Few Shot Time Series Forecasting
336. ICML 2025Geometric Feature Embedding for Effective 3D Few-Shot Class Incremental Learning
337. ICML 2025GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance
338. ICML 2025MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning
339. ICML 2025On the Provable Separation of Scales in Maximal Update Parameterization
340. ICML 2025One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models
341. ICML 2025PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs
342. ICML 2025Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning
343. ICML 2025Position: Don't Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints
344. ICML 2025Provable Zero-Shot Generalization in Offline Reinforcement Learning
345. ICML 2025Provably Improving Generalization of Few-shot models with Synthetic Data
346. ICML 2025Quantifying Prediction Consistency Under Fine-tuning Multiplicity in Tabular LLMs
347. ICML 2025Random Registers for Cross-Domain Few-Shot Learning
348. ICML 2025Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning
349. ICML 2025Revisiting Neural Networks for Few-Shot Learning: A Zero-Cost NAS Perspective
350. ICML 2025SAND: One-Shot Feature Selection with Additive Noise Distortion

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.