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 168 篇，第 3 / 4 页

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

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。