小样本学习论文趋势 2023–2026

元学习与小样本

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 898 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

小样本学习论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202376564079251
202464383781220
202568363564203
202651385679224

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

全部小样本学习论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 251 篇，第 4 / 6 页

  1. ICML 2023GeCoNeRF: Few-shot Neural Radiance Fields via Geometric Consistency
  2. ICML 2023HyperTuning: Toward Adapting Large Language Models without Back-propagation
  3. ICML 2023Interval Bound Interpolation for Few-shot Learning with Few Tasks
  4. ICML 2023Learning the Dynamics of Sparsely Observed Interacting Systems
  5. ICML 2023Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
  6. ICML 2023Lifelong Language Pretraining with Distribution-Specialized Experts
  7. ICML 2023Meta Optimal Transport
  8. ICML 2023Meta-learning Parameterized Skills
  9. ICML 2023Meta-Learning the Inductive Bias of Simple Neural Circuits
  10. ICML 2023MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks
  11. ICML 2023MEWL: Few-shot multimodal word learning with referential uncertainty
  12. ICML 2023Model-agnostic Measure of Generalization Difficulty
  13. ICML 2023One-Shot Federated Conformal Prediction
  14. ICML 2023One-shot Imitation in a Non-Stationary Environment via Multi-Modal Skill
  15. ICML 2023Online Prototype Alignment for Few-shot Policy Transfer
  16. ICML 2023PreNAS: Preferred One-Shot Learning Towards Efficient Neural Architecture Search
  17. ICML 2023Reward-Mixing MDPs with Few Latent Contexts are Learnable
  18. ICML 2023SemSup-XC: Semantic Supervision for Zero and Few-shot Extreme Classification
  19. ICML 2023Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning
  20. ICML 2023SparseGPT: Massive Language Models Can be Accurately Pruned in One-Shot
  21. ICML 2023The Unreasonable Effectiveness of Few-shot Learning for Machine Translation
  22. ICML 2023Towards Controlled Data Augmentations for Active Learning
  23. ICML 2023Tuning Language Models as Training Data Generators for Augmentation-Enhanced Few-Shot Learning
  24. ICML 2023Uncertainty Estimation by Fisher Information-based Evidential Deep Learning
  25. ICML 2023Variance Control for Distributional Reinforcement Learning
  26. NeurIPS 2023A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm
  27. NeurIPS 2023A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence
  28. NeurIPS 2023Alignment with human representations supports robust few-shot learning
  29. NeurIPS 2023An Efficient Dataset Condensation Plugin and Its Application to Continual Learning
  30. NeurIPS 2023Context Shift Reduction for Offline Meta-Reinforcement Learning
  31. NeurIPS 2023Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes
  32. NeurIPS 2023Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL
  33. NeurIPS 2023CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion
  34. NeurIPS 2023DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation
  35. NeurIPS 2023Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks
  36. NeurIPS 2023DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation
  37. NeurIPS 2023Domain Re-Modulation for Few-Shot Generative Domain Adaptation
  38. NeurIPS 2023EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
  39. NeurIPS 2023Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
  40. NeurIPS 2023Explore to Generalize in Zero-Shot RL
  41. NeurIPS 2023Exploring Diverse In-Context Configurations for Image Captioning
  42. NeurIPS 2023ExPT: Synthetic Pretraining for Few-Shot Experimental Design
  43. NeurIPS 2023Extensible Prompts for Language Models on Zero-shot Language Style Customization
  44. NeurIPS 2023Fairness-guided Few-shot Prompting for Large Language Models
  45. NeurIPS 2023FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning
  46. NeurIPS 2023FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning
  47. NeurIPS 2023Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration
  48. NeurIPS 2023Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory
  49. NeurIPS 2023Focus on Query: Adversarial Mining Transformer for Few-Shot Segmentation
  50. NeurIPS 2023Focus Your Attention when Few-Shot Classification

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查小样本学习在 CVPR 2023–2026 的论文趋势，哪一年涨得最快？

AI 会调用的工具：get_topic_stats {"topic": "few-shot-learning"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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