联邦学习论文趋势 2023–2026

跨设备联邦

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 460 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

联邦学习论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202354293420137
202430234020113
20253118231991
202642193721119

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

全部联邦学习论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 80 篇，第 2 / 2 页

  1. CVPR 2024FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning
  2. CVPR 2024FLHetBench: Benchmarking Device and State Heterogeneity in Federated Learning
  3. CVPR 2024Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices
  4. CVPR 2024Motion Blur Decomposition with Cross-shutter Guidance
  5. CVPR 2024Relaxed Contrastive Learning for Federated Learning
  6. CVPR 2024Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data
  7. CVPR 2024Revamping Federated Learning Security from a Defender's Perspective: A Unified Defense with Homomorphic Encrypted Data Space
  8. CVPR 2024Text-Enhanced Data-free Approach for Federated Class-Incremental Learning
  9. CVPR 2024Towards Efficient Replay in Federated Incremental Learning
  10. CVPR 2024Traceable Federated Continual Learning
  11. CVPR 2023Adaptive Channel Sparsity for Federated Learning Under System Heterogeneity
  12. CVPR 2023Bias-Eliminating Augmentation Learning for Debiased Federated Learning
  13. CVPR 2023Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization
  14. CVPR 2023DaFKD: Domain-Aware Federated Knowledge Distillation
  15. CVPR 2023Efficient On-Device Training via Gradient Filtering
  16. CVPR 2023FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning
  17. CVPR 2023Federated Domain Generalization With Generalization Adjustment
  18. CVPR 2023Federated Incremental Semantic Segmentation
  19. CVPR 2023Federated Learning With Data-Agnostic Distribution Fusion
  20. CVPR 2023FedSeg: Class-Heterogeneous Federated Learning for Semantic Segmentation
  21. CVPR 2023GradMA: A Gradient-Memory-Based Accelerated Federated Learning With Alleviated Catastrophic Forgetting
  22. CVPR 2023How To Prevent the Poor Performance Clients for Personalized Federated Learning?
  23. CVPR 2023Learning Federated Visual Prompt in Null Space for MRI Reconstruction
  24. CVPR 2023Make Landscape Flatter in Differentially Private Federated Learning
  25. CVPR 2023On the Effectiveness of Partial Variance Reduction in Federated Learning With Heterogeneous Data
  26. CVPR 2023Re-Thinking Federated Active Learning Based on Inter-Class Diversity
  27. CVPR 2023Rethinking Federated Learning With Domain Shift: A Prototype View
  28. CVPR 2023ScaleFL: Resource-Adaptive Federated Learning With Heterogeneous Clients
  29. CVPR 2023STDLens: Model Hijacking-Resilient Federated Learning for Object Detection
  30. CVPR 2023The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning

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 查联邦学习在 NeurIPS 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": "federated-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联邦学习论文？
共 460 篇，按年份分别是 2023 年 137 篇、2024 年 113 篇、2025 年 91 篇、2026 年 119 篇。
NeurIPS 2026 有多少篇联邦学习论文？
NeurIPS 2026 有 42 篇联邦学习论文，上一届是 31 篇。
ICLR 2026 有多少篇联邦学习论文？
ICLR 2026 有 19 篇联邦学习论文，上一届是 18 篇。
ICML 2026 有多少篇联邦学习论文？
ICML 2026 有 37 篇联邦学习论文，上一届是 23 篇。
CVPR 2026 有多少篇联邦学习论文？
CVPR 2026 有 21 篇联邦学习论文，上一届是 19 篇。
哪个会议的联邦学习论文最多？
NeurIPS，2023–2026 年共 157 篇。

「联邦与隐私」下的其他主题