Learning Paradigms
14,967 papers (9 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Transfer Learning (8,172)
Few-Shot Learning (2,681)
Meta-Learning (1,719)
Federated Learning (1,560)
Zero-Shot Learning (878)
Continual Learning (189)
Domain Adaptation (184)
Self-Supervised Learning (158)
Active Learning (154)
Multi-Task Learning (145)
Semi-Supervised Learning (86)
In-Context Learning (53)
Unsupervised Learning (53)
Domain Generalization (26)
Weakly Supervised Learning (23)
Papers per year
3
2
4
12
24
14
20
29
31
32
66
53
67
103
206
482
852
1,124
1,566
1,867
2,410
2,658
2,486
856
'5
'10
'15
'20
'25
Papers (including subtopics)
Federated Model Synchronization for Diagnostic Redefinition through a Novel Selective Parameter Unlearning
WACV 2026
Federated Vision-Language-Recommendation with Personalized Fusion
AAAI 2026
FedGRPO: Privately Optimizing Foundation Models with Group-Relative Rewards from Domain Clients
AAAI 2026
FedLAGC: Towards High Performance System-Heterogeneous Federated Learning via Layer-Adaptive Submodel Extraction and Gradient Correction
AAAI 2026
FedMental: Evaluating Federated Learning for Mental Health Detection from Social Media Data
ACL 2026
FedMerge: Federated Model Merging for Personalization
AAAI 2026
FedMOP: Achieving Enhanced Privacy and Performance in Federated Learning via Momentum Orthogonal Projection
CVPR 2026
FedP²EFT: Federated Learning to Personalize PEFT for Multilingual LLMs
AAAI 2026
FedPKDA: Personalized Federated Learning with Privacy-Preserving Knowledge Dynamic Alignment
AAAI 2026
FedPM: Federated Learning Using Second-order Optimization with Preconditioned Mixing of Local Parameters
AAAI 2026
FedRAC: Rolling Submodel Allocation for Collaborative Fairness in Federated Learning
CVPR 2026
FedRE: A Representation Entanglement Framework for Model-Heterogeneous Federated Learning
CVPR 2026
FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation
EACL 2026
FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients
CVPR 2026
FedRNC: Addressing Spatio-Temporal Label Misalignment in Federated Noisy Class-Incremental Learning
AAAI 2026
FedSCAl: Leveraging Server and Client Alignment for Unsupervised Federated Source-Free Domain Adaptation
WACV 2026
FedSDWC: Federated Synergistic Dual-Representation Weak Causal Learning for OOD
AAAI 2026
FedSEA-LLaMA: A Secure, Efficient and Adaptive Federated Splitting Framework for Large Language Models
AAAI 2026
FedShard: Federated Unlearning with Efficiency Fairness and Performance Fairness
AAAI 2026
FedSkeleton: Secure Multi-Party Graph Skeleton Construction for Privacy-Preserving Federated Time-Series Forecasting
AAAI 2026
FedSteer: Taming Extreme Gradient Staleness in Federated Learning with Corrective Projections and Caching
UAI 2026
FedTopo: Topology-Informed Representation Alignment in Federated Learning Under Non-I.I.D. Conditions
AAAI 2026
Few-Shot Hybrid Incremental Learning:Continually Learning under Data Scarcity and Task Uncertainty
CVPR 2026
FGNet: Leveraging Feature-Guided Attention to Refine SAM2 for 3D EM Neuron Segmentation
AAAI 2026
FILTER: A Framework for Defending Against Backdoor Attacks in Vertical Federated Learning
AAAI 2026