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 30 篇，第 1 / 1 页

  1. NeurIPS 2024A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings
  2. NeurIPS 2024A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs
  3. NeurIPS 2024Bridging Gaps: Federated Multi-View Clustering in Heterogeneous Hybrid Views
  4. NeurIPS 2024Confusion-Resistant Federated Learning via Diffusion-Based Data Harmonization on Non-IID Data
  5. NeurIPS 2024DataStealing: Steal Data from Diffusion Models in Federated Learning with Multiple Trojans
  6. NeurIPS 2024Does Egalitarian Fairness Lead to Instability? The Fairness Bounds in Stable Federated Learning Under Altruistic Behaviors
  7. NeurIPS 2024FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding?
  8. NeurIPS 2024FedAvP: Augment Local Data via Shared Policy in Federated Learning
  9. NeurIPS 2024Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning
  10. NeurIPS 2024Federated Ensemble-Directed Offline Reinforcement Learning
  11. NeurIPS 2024Federated Graph Learning for Cross-Domain Recommendation
  12. NeurIPS 2024Federated Learning over Connected Modes
  13. NeurIPS 2024Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis
  14. NeurIPS 2024Federated Model Heterogeneous Matryoshka Representation Learning
  15. NeurIPS 2024FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning
  16. NeurIPS 2024FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation
  17. NeurIPS 2024Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity
  18. NeurIPS 2024FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion
  19. NeurIPS 2024Hierarchical Federated Learning with Multi-Timescale Gradient Correction
  20. NeurIPS 2024Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning
  21. NeurIPS 2024Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data
  22. NeurIPS 2024Parameter Disparities Dissection for Backdoor Defense in Heterogeneous Federated Learning
  23. NeurIPS 2024pFedClub: Controllable Heterogeneous Model Aggregation for Personalized Federated Learning
  24. NeurIPS 2024Revisiting Ensembling in One-Shot Federated Learning
  25. NeurIPS 2024SPEAR: Exact Gradient Inversion of Batches in Federated Learning
  26. NeurIPS 2024Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains
  27. NeurIPS 2024The Power of Extrapolation in Federated Learning
  28. NeurIPS 2024The Sample-Communication Complexity Trade-off in Federated Q-Learning
  29. NeurIPS 2024Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration
  30. NeurIPS 2024Why Go Full? Elevating Federated Learning Through Partial Network Updates

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。

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