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 897 篇，第 12 / 18 页

  1. ICML 2024Bidirectional Reciprocative Information Communication for Few-Shot Semantic Segmentation
  2. ICML 2024Byzantine Resilient and Fast Federated Few-Shot Learning
  3. ICML 2024Can a Few Decide for Many? The Metric Distortion of Sortition
  4. ICML 2024Compositional Few-Shot Class-Incremental Learning
  5. ICML 2024DMTG: One-Shot Differentiable Multi-Task Grouping
  6. ICML 2024Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods
  7. ICML 2024Enabling Few-Shot Learning with PID Control: A Layer Adaptive Optimizer
  8. ICML 2024Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings
  9. ICML 2024Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind
  10. ICML 2024Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries
  11. ICML 2024Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations
  12. ICML 2024Hyperbolic Optimizer as a Dynamical System
  13. ICML 2024Implicit meta-learning may lead language models to trust more reliable sources
  14. ICML 2024In-Context Unlearning: Language Models as Few-Shot Unlearners
  15. ICML 2024Language-Driven Cross-Modal Classifier for Zero-Shot Multi-Label Image Recognition
  16. ICML 2024Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning
  17. ICML 2024Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition
  18. ICML 2024Learning Multiple Secrets in Mastermind
  19. ICML 2024Learning to Route Among Specialized Experts for Zero-Shot Generalization
  20. ICML 2024MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent
  21. ICML 2024Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games
  22. ICML 2024MD tree: a model-diagnostic tree grown on loss landscape
  23. ICML 2024Meta Evidential Transformer for Few-Shot Open-Set Recognition
  24. ICML 2024MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence
  25. ICML 2024More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
  26. ICML 2024One Meta-tuned Transformer is What You Need for Few-shot Learning
  27. ICML 2024One-Shot Strategic Classification Under Unknown Costs
  28. ICML 2024PID: Prompt-Independent Data Protection Against Latent Diffusion Models
  29. ICML 2024Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss
  30. ICML 2024The Balanced-Pairwise-Affinities Feature Transform
  31. ICML 2024Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts
  32. ICML 2024Zero-Shot Reinforcement Learning via Function Encoders
  33. NeurIPS 2024(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning
  34. NeurIPS 2024A Closer Look at the CLS Token for Cross-Domain Few-Shot Learning
  35. NeurIPS 2024A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation
  36. NeurIPS 2024A Simple yet Universal Framework for Depth Completion
  37. NeurIPS 2024A Surprisingly Simple Approach to Generalized Few-Shot Semantic Segmentation
  38. NeurIPS 2024Active Classification with Few Queries under Misspecification
  39. NeurIPS 2024AED: Adaptable Error Detection for Few-shot Imitation Policy
  40. NeurIPS 2024An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning
  41. NeurIPS 2024Attention Temperature Matters in ViT-Based Cross-Domain Few-Shot Learning
  42. NeurIPS 2024AutoMix: Automatically Mixing Language Models
  43. NeurIPS 2024Boosting Vision-Language Models with Transduction
  44. NeurIPS 2024Bridge the Points: Graph-based Few-shot Segment Anything Semantically
  45. NeurIPS 2024CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset
  46. NeurIPS 2024Class Distribution Shifts in Zero-Shot Learning: Learning Robust Representations
  47. NeurIPS 2024Combining Observational Data and Language for Species Range Estimation
  48. NeurIPS 2024Concentrate Attention: Towards Domain-Generalizable Prompt Optimization for Language Models
  49. NeurIPS 2024D2R2: Diffusion-based Representation with Random Distance Matching for Tabular Few-shot Learning
  50. NeurIPS 2024Dendritic Integration Inspired Artificial Neural Networks Capture Data Correlation

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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