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

共 168 篇,第 1 / 4 页

  1. ICML 2026Bayes-inspired Integration of Pretrained Priors and Few-Shot Evidence for Few-Shot Classification
  2. ICML 2026Benchmarking Dense and Indiscernible Object Counting with Blueberries
  3. ICML 2026Beyond Description: Federated Adaptation via Semantic-Visual Prototype Alignment
  4. ICML 2026BiCrossNet with Decoupled Dual Generators: A Parameter‑Efficient and Generalizable Few‑Shot Custom Gesture Recognition Framework
  5. ICML 2026Breaking the Scale Barrier: One-Shot Knowledge Transfer via Frequency Transform
  6. ICML 2026Calibrating Uncertainty for Zero-Shot Adversarial CLIP
  7. ICML 2026CAOS: Conformal Aggregation of One-Shot Predictors
  8. ICML 2026Consistent Zero-Shot Imitation with Contrastive Goal Inference
  9. ICML 2026Decision Transformers As Zero-Shot Learners via Text-Behavior Alignment
  10. ICML 2026DiP-G: Discrete Prompting for Graph Neural Networks
  11. ICML 2026Directional Neural Collapse Explains Few-Shot Transfer in Self-Supervised Learning
  12. ICML 2026Distribution Alignment for One-Shot Federated Learning via Optimal Transport
  13. ICML 2026DNA: Uncovering Universal Latent Forgery Knowledge
  14. ICML 2026Few-Shot Design Optimization by Exploiting Auxiliary Information
  15. ICML 2026Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models
  16. ICML 2026Fleet: Few Shots Lead Effective AI-generated Image Detection
  17. ICML 2026From Coarse to Fine: Deep Prototype Refinement Network for Few-Shot Point Cloud Semantic Segmentation
  18. ICML 2026Geometry-Aware Contrastive Learning for Few-Shot Automatic Modulation Recognition
  19. ICML 2026Harnessing Spectrum Video for Subject-Level Few-Shot and Cross-Montage EEG Generalization
  20. ICML 2026Hedging on the Frontier: Learning New Tasks with Few Samples
  21. ICML 2026How Few-Shot Examples Add Up: A Causal Decomposition of Function Vectors in In-Context Learning
  22. ICML 2026Improving CLIP Adaptation by Breaking Tail Alignment for Source-Free Cross-Domain Few-Shot Learning
  23. ICML 2026Infinite Mask Diffusion for Few-Step Distillation
  24. ICML 2026InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate
  25. ICML 2026Keep Everyone Happy: Online Fair Division of Numerous Items with Few Copies
  26. ICML 2026Lottery Prior: Randomized Neural Compression for Zero-Shot Inverse Problems
  27. ICML 2026Many Experiments, Few Repetitions, Unpaired Data, and Sparse Effects: Is Causal Inference Possible?
  28. ICML 2026Meta-learning Structure-Preserving Dynamics
  29. ICML 2026Mitigating the Contractivity Trap in Diffusion ODEs via Stein Stabilization
  30. ICML 2026Motion Dynamics Learning for Few-Shot Embodied Adaptation
  31. ICML 2026On the Expressive Power of Permutation-Equivariant Weight-Space Networks
  32. ICML 2026One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models
  33. ICML 2026One-shot Conditional Sampling: MMD meets Nearest Neighbors
  34. ICML 2026One-Shot Weighted Ensemble Estimation for Federated Quantile Regression: Optimal Statistical Guarantees under Heterogeneous Structured Data
  35. ICML 2026Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning
  36. ICML 2026Path-Decoupled Hyperbolic Flow Matching for Few-Shot Adaptation
  37. ICML 2026Prompt Tuning for CLIP on the Pretrained Manifold
  38. ICML 2026Rank-guided Diffusion for Noise Few-Shot Learning
  39. ICML 2026Reasoning Can Be Restored by Correcting a Few Decision Tokens
  40. ICML 2026ReAugment: Targeted Few-Shot Time Series Augmentation via Model Zoo-Guided Reinforcement Learning
  41. ICML 2026ReCoG: Relational and Compact Context Graph Learning for Few-shot Molecular Property Prediction
  42. ICML 2026Remove the Ambiguity: Few-shot Multimodal Anomaly Detection Using Crossmodal Feature Replacers
  43. ICML 2026SEMIR: Semantic Minor-Induced Representation Learning on Graphs for Visual Segmentation
  44. ICML 2026SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot
  45. ICML 2026Structure-Centric Graph Foundation Model via Geometric Bases
  46. ICML 2026Structured Expert Routing with Multi-View Task Priors for Offline Meta-Reinforcement Learning
  47. ICML 2026The Hippocampal Place Field Gradient: A Bio-inspired Framework Building Multiscale Representation for Better Sample Efficiency
  48. ICML 2026Theoretical Guarantees for One-Shot Magnitude Pruning and Compute-Adaptive Early Exit
  49. ICML 2026Tiny Brains, Giant Impact: Uncovering the Keystone Neurons of LLM with Just a Few Prompts
  50. ICML 2026Towards a Unified Generative Model for Scarce Time Series with Domain Experts

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"}

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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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