小样本学习论文趋势 2023–2026

主要结论

• 小样本学习论文从 2023 年的 251 篇降到 2026 年的 224 篇，热度在回落。
• CVPR 是发小样本学习论文最多的会议，2023–2026 年共 303 篇，占四个会议总量的 34%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 4 篇增至 2026 年的 24 篇。
• 在「元学习与迁移」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的基础模型适配是 3.8 倍，小样本学习是 0.9 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部小样本学习论文

共 220 篇，第 3 / 5 页

101. ICLR 2024Information Retention via Learning Supplemental Features
102. ICLR 2024Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages
103. ICLR 2024Meta-Learning Priors Using Unrolled Proximal Networks
104. ICLR 2024MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation
105. ICLR 2024MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images
106. ICLR 2024Neural Fine-Tuning Search for Few-Shot Learning
107. ICLR 2024One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models
108. ICLR 2024One-shot Empirical Privacy Estimation for Federated Learning
109. ICLR 2024Overthinking the Truth: Understanding how Language Models Process False Demonstrations
110. ICLR 2024Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
111. ICLR 2024Personalize Segment Anything Model with One Shot
112. ICLR 2024Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
113. ICLR 2024Scalable Language Model with Generalized Continual Learning
114. ICLR 2024Spatio-Temporal Few-Shot Learning via Diffusive Neural Network Generation
115. ICLR 2024TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models
116. ICLR 2024Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning
117. ICLR 2024Zero and Few-shot Semantic Parsing with Ambiguous Inputs
118. ICLR 2024Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models
119. ICLR 2024Zero-Shot Robustification of Zero-Shot Models
120. ICML 2024Accelerating Convergence in Bayesian Few-Shot Classification
121. ICML 2024Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving
122. ICML 2024Agent Instructs Large Language Models to be General Zero-Shot Reasoners
123. ICML 2024Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities
124. ICML 2024Balancing Feature Similarity and Label Variability for Optimal Size-Aware One-shot Subset Selection
125. ICML 2024Bidirectional Reciprocative Information Communication for Few-Shot Semantic Segmentation
126. ICML 2024Byzantine Resilient and Fast Federated Few-Shot Learning
127. ICML 2024Can a Few Decide for Many? The Metric Distortion of Sortition
128. ICML 2024Compositional Few-Shot Class-Incremental Learning
129. ICML 2024DMTG: One-Shot Differentiable Multi-Task Grouping
130. ICML 2024Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods
131. ICML 2024Enabling Few-Shot Learning with PID Control: A Layer Adaptive Optimizer
132. ICML 2024Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings
133. ICML 2024Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind
134. ICML 2024Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries
135. ICML 2024Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations
136. ICML 2024Hyperbolic Optimizer as a Dynamical System
137. ICML 2024Implicit meta-learning may lead language models to trust more reliable sources
138. ICML 2024In-Context Unlearning: Language Models as Few-Shot Unlearners
139. ICML 2024Language-Driven Cross-Modal Classifier for Zero-Shot Multi-Label Image Recognition
140. ICML 2024Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning
141. ICML 2024Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition
142. ICML 2024Learning Multiple Secrets in Mastermind
143. ICML 2024Learning to Route Among Specialized Experts for Zero-Shot Generalization
144. ICML 2024MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent
145. ICML 2024Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games
146. ICML 2024MD tree: a model-diagnostic tree grown on loss landscape
147. ICML 2024Meta Evidential Transformer for Few-Shot Open-Set Recognition
148. ICML 2024MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence
149. ICML 2024More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
150. ICML 2024One Meta-tuned Transformer is What You Need for Few-shot Learning

常见问题

2023–2026 年四大会议一共有多少篇小样本学习论文？

共 898 篇，按年份分别是 2023 年 251 篇、2024 年 220 篇、2025 年 203 篇、2026 年 224 篇。

NeurIPS 2026 有多少篇小样本学习论文？

NeurIPS 2026 有 51 篇小样本学习论文，上一届是 68 篇。

ICLR 2026 有多少篇小样本学习论文？

ICLR 2026 有 38 篇小样本学习论文，上一届是 36 篇。

ICML 2026 有多少篇小样本学习论文？

ICML 2026 有 56 篇小样本学习论文，上一届是 35 篇。

CVPR 2026 有多少篇小样本学习论文？

CVPR 2026 有 79 篇小样本学习论文，上一届是 64 篇。

哪个会议的小样本学习论文最多？

CVPR，2023–2026 年共 303 篇。