Federated Learning papers, 2023–2026

Key findings

• Federated Learning fell from 137 papers in 2023 to 119 in 2026, so interest is cooling.
• NeurIPS publishes the most Federated Learning work: 157 papers from 2023 to 2026, 34% of the four-venue total.
• The fastest-growing overlap is with Low-Rank Adaptation: papers tagged with both rose from 0 in 2023 to 12 in 2026.
• Among the 5 topics under Federated and Privacy, it ranks #2 by 2026 paper count; the fastest grower in the group, Secure Aggregation, is up 1.8x versus 0.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A typed tensor language for federated learning
• ICML 2026BESplit: Bias-Compensated Split Federated Learning with Evidential Aggregation
• ICLR 2026Beyond Aggregation: Guiding Clients in Heterogeneous Federated Learning
• CVPR 2026FedRG Unleashing the Representation Geometry for Federated Learning with Noisy
• NeurIPS 2025Class-wise Balancing Data Replay for Federated Class-Incremental Learning
• ICML 2025Causality Inspired Federated Learning for OOD Generalization
• ICLR 2025Adaptive Gradient Clipping for Robust Federated Learning
• CVPR 2025FedCS: Coreset Selection for Federated Learning
• NeurIPS 2024Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning
• ICML 2024Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning
• ICLR 2024FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning
• CVPR 2024Decentralized Directed Collaboration for Personalized Federated Learning
• NeurIPS 2023DELTA: Diverse Client Sampling for Fasting Federated Learning
• ICML 2023Achieving Linear Speedup in Non-IID Federated Bilevel Learning
• ICLR 2023Combating Exacerbated Heterogeneity for Robust Models in Federated Learning
• CVPR 2023Federated Domain Generalization With Generalization Adjustment
• NeurIPS 2026Consistency-Verified Backdoor Defense for Federated Graph Learning via Cross-Layer Drift
• ICML 2026Breaking the Capacity Bottleneck in Model-Heterogeneous Federated Learning via Gradual Model Restoration
• ICLR 2026DeepAFL: Deep Analytic Federated Learning
• CVPR 2026FedSST Rethinking Fair Federated Graph Learning under Structural Shift

All Federated Learning papers

80 papers, page 1 of 2

1. CVPR 2026Batman Benign Knowledge Alignment Through Malicious Null Space in Federated
2. CVPR 2026Controllable Federated Prompt Learning at Test Time
3. CVPR 2026Domain Sensitive Federated Learning with Fisher-Informed Pruning
4. CVPR 2026DP-FedAdamW An Efficient Optimizer for Differentially Private Federated Large Models
5. CVPR 2026FedAlign Differentially Private Distribution Alignment for Non-IID Federated Learning
6. CVPR 2026FedBPrompt Federated Domain Generalization Person Re-Identification via Body Distribution Aware
7. CVPR 2026FedCART Tackling Long-Tailed Distributions in Federated Adversarial Training via Classifier
8. CVPR 2026FedDAP Domain-Aware Prototype Learning for Federated Learning under Domain Shift
9. CVPR 2026FedHarmony Harmonizing Heterogeneous Label Correlations in Federated Multi-Label Learning
10. CVPR 2026FedRAC Rolling Submodel Allocation for Collaborative Fairness in Federated Learning
11. CVPR 2026FedRE A Representation Entanglement Framework for Model-Heterogeneous Federated Learning
12. CVPR 2026FedRG Unleashing the Representation Geometry for Federated Learning with Noisy
13. CVPR 2026FedSST Rethinking Fair Federated Graph Learning under Structural Shift
14. CVPR 2026Few-for-Many Personalized Federated Learning
15. CVPR 2026From Selection to Scheduling Federated Geometry-Aware Correction Makes Exemplar Replay
16. CVPR 2026GDFA Geometry-Driven Federated Unlearning with Directional Task Vector Alignment
17. CVPR 2026HiLoRA Hierarchical Low-Rank Adaptation for Personalized Federated Learning
18. CVPR 2026Pose-guided Enriched Feature Learning for Federated-by-camera Person Re-identification
19. CVPR 2026ProxyFL A Proxy-Guided Framework for Federated Semi-Supervised Learning
20. CVPR 2026RHO Robust Holistic OSM-Based Metric Cross-View Geo-Localization
21. CVPR 2026Single-Round Scalable Analytic Federated Learning
22. CVPR 2025A Simple Data Augmentation for Feature Distribution Skewed Federated Learning
23. CVPR 2025AFL: A Single-Round Analytic Approach for Federated Learning with Pre-trained Models
24. CVPR 2025CroCoDL: Cross-device Collaborative Dataset for Localization
25. CVPR 2025dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis
26. CVPR 2025FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors
27. CVPR 2025FedCALM: Conflict-aware Layer-wise Mitigation for Selective Aggregation in Deeper Personalized Federated Learning
28. CVPR 2025FedCS: Coreset Selection for Federated Learning
29. CVPR 2025Federated Learning with Domain Shift Eraser
30. CVPR 2025FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning
31. CVPR 2025FedSPA: Generalizable Federated Graph Learning under Homophily Heterogeneity
32. CVPR 2025Geometric Knowledge-Guided Localized Global Distribution Alignment for Federated Learning
33. CVPR 2025Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor
34. CVPR 2025HistoFS: Non-IID Histopathologic Whole Slide Image Classification via Federated Style Transfer with RoI-Preserving
35. CVPR 2025Infighting in the Dark: Multi-Label Backdoor Attack in Federated Learning
36. CVPR 2025Mind the Gap: Confidence Discrepancy Can Guide Federated Semi-Supervised Learning Across Pseudo-Mismatch
37. CVPR 2025NoT: Federated Unlearning via Weight Negation
38. CVPR 2025pFedMxF: Personalized Federated Class-Incremental Learning with Mixture of Frequency Aggregation
39. CVPR 2025Population Normalization for Federated Learning
40. CVPR 2025Unlearning through Knowledge Overwriting: Reversible Federated Unlearning via Selective Sparse Adapter
41. CVPR 2024An Aggregation-Free Federated Learning for Tackling Data Heterogeneity
42. CVPR 2024Communication-Efficient Federated Learning with Accelerated Client Gradient
43. CVPR 2024Decentralized Directed Collaboration for Personalized Federated Learning
44. CVPR 2024Device-Wise Federated Network Pruning
45. CVPR 2024FedAS: Bridging Inconsistency in Personalized Federated Learning
46. CVPR 2024Federated Generalized Category Discovery
47. CVPR 2024Federated Online Adaptation for Deep Stereo
48. CVPR 2024FedHCA2: Towards Hetero-Client Federated Multi-Task Learning
49. CVPR 2024FedMef: Towards Memory-efficient Federated Dynamic Pruning
50. CVPR 2024FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning

FAQ

How many Federated Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

460 in total: 137 in 2023, 113 in 2024, 91 in 2025, 119 in 2026.

How many Federated Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 42 Federated Learning papers, versus 31 the year before.

How many Federated Learning papers are at ICLR 2026?

ICLR 2026 has 19 Federated Learning papers, versus 18 the year before.

How many Federated Learning papers are at ICML 2026?

ICML 2026 has 37 Federated Learning papers, versus 23 the year before.

How many Federated Learning papers are at CVPR 2026?

CVPR 2026 has 21 Federated Learning papers, versus 19 the year before.

Which conference publishes the most Federated Learning papers?

NeurIPS, with 157 papers from 2023 to 2026.