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 203 篇，第 3 / 5 页

101. ICML 2025Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
102. ICML 2025Adaptive Multi-prompt Contrastive Network for Few-shot Out-of-distribution Detection
103. ICML 2025Alpha-SQL: Zero-Shot Text-to-SQL using Monte Carlo Tree Search
104. ICML 2025Bootstrapping Self-Improvement of Language Model Programs for Zero-Shot Schema Matching
105. ICML 2025CERTAIN: Context Uncertainty-aware One-Shot Adaptation for Context-based Offline Meta Reinforcement Learning
106. ICML 2025Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated Learning
107. ICML 2025DyPolySeg: Taylor Series-Inspired Dynamic Polynomial Fitting Network for Few-shot Point Cloud Semantic Segmentation
108. ICML 2025FedBEns: One-Shot Federated Learning based on Bayesian Ensemble
109. ICML 2025Federated Oriented Learning: A Practical One-Shot Personalized Federated Learning Framework
110. ICML 2025Feedforward Few-shot Species Range Estimation
111. ICML 2025Few-Shot Learner Generalizes Across AI-Generated Image Detection
112. ICML 2025FSTLLM: Spatio-Temporal LLM for Few Shot Time Series Forecasting
113. ICML 2025Geometric Feature Embedding for Effective 3D Few-Shot Class Incremental Learning
114. ICML 2025GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance
115. ICML 2025MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning
116. ICML 2025On the Provable Separation of Scales in Maximal Update Parameterization
117. ICML 2025One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models
118. ICML 2025PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs
119. ICML 2025Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning
120. ICML 2025Position: Don't Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints
121. ICML 2025Provable Zero-Shot Generalization in Offline Reinforcement Learning
122. ICML 2025Provably Improving Generalization of Few-shot models with Synthetic Data
123. ICML 2025Quantifying Prediction Consistency Under Fine-tuning Multiplicity in Tabular LLMs
124. ICML 2025Random Registers for Cross-Domain Few-Shot Learning
125. ICML 2025Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning
126. ICML 2025Revisiting Neural Networks for Few-Shot Learning: A Zero-Cost NAS Perspective
127. ICML 2025SAND: One-Shot Feature Selection with Additive Noise Distortion
128. ICML 2025Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
129. ICML 2025Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation
130. ICML 2025SLiM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression
131. ICML 2025The Missing Alignment Link of In-context Learning on Sequences
132. ICML 2025The Surprising Effectiveness of Test-Time Training for Few-Shot Learning
133. ICML 2025Unlocking the Power of SAM 2 for Few-Shot Segmentation
134. ICML 2025Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer
135. ICML 2025Zero-Shot Offline Imitation Learning via Optimal Transport
136. NeurIPS 2025A Few Moments Please: Scalable Graphon Learning via Moment Matching
137. NeurIPS 2025An Effective Levelling Paradigm for Unlabeled Scenarios
138. NeurIPS 2025Attack via Overfitting: 10-shot Benign Fine-tuning to Jailbreak LLMs
139. NeurIPS 2025Blackbox Model Provenance via Palimpsestic Membership Inference
140. NeurIPS 2025Dataset Distillation for Pre-Trained Self-Supervised Vision Models
141. NeurIPS 2025DETree: DEtecting Human-AI Collaborative Texts via Tree-Structured Hierarchical Representation Learning
142. NeurIPS 2025Diffusion-Classifier Synergy: Reward-Aligned Learning via Mutual Boosting Loop for FSCIL
143. NeurIPS 2025Domain-Specific Pruning of Large Mixture-of-Experts Models with Few-shot Demonstrations
144. NeurIPS 2025DON’T NEED RETRAINING: A Mixture of DETR and Vision Foundation Models for Cross-Domain Few-Shot Object Detection
145. NeurIPS 2025Dual Alignment Framework for Few-shot Learning with Inter-Set and Intra-Set Shifts
146. NeurIPS 2025Enhancing Zero-Shot Black-Box Optimization via Pretrained Models with Efficient Population Modeling, Interaction, and Stable Gradient Approximation
147. NeurIPS 2025Evolving and Regularizing Meta-Environment Learner for Fine-Grained Few-Shot Class-Incremental Learning
148. NeurIPS 2025Fast exact recovery of noisy matrix from few entries: the infinity norm approach
149. NeurIPS 2025Few-Shot Knowledge Distillation of LLMs With Counterfactual Explanations
150. NeurIPS 2025Few-Shot Learning from Gigapixel Images via Hierarchical Vision-Language Alignment and Modeling

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。