Federated Learning
1,560 papers
Papers per year
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1
7
2
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4
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13
20
77
143
228
328
289
306
130
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'25
Papers
Scalable Federated One-Step Multi-View Clustering with Tensorized Regularization
AAAI 2025
Secure On-Device Video OOD Detection Without Backpropagation
ICCV 2025
Selective Aggregation for Low-Rank Adaptation in Federated Learning
ICLR 2025
Selective Inference with Distributed Data
JMLR 2025
Sharp Bounds for Sequential Federated Learning on Heterogeneous Data
JMLR 2025
Sibai: A Few-Shot Meta-Classifier for Poisoning Detection in Federated Learning
ICCV 2025
Sim911: Towards Effective and Equitable 9-1-1 Dispatcher Training with an LLM-Enabled Simulation
AAAI 2025
Simple Yet Effective: Extracting Private Data Across Clients in Federated Fine-Tuning of Large Language Models
IJCNLP 2025
Single-Loop Federated Actor-Critic across Heterogeneous Environments
AAAI 2025
Some Targets Are Harder to Identify than Others: Quantifying the Target-dependent Membership Leakage
AISTATS 2025
SparsyFed: Sparse Adaptive Federated Learning
ICLR 2025
Split Adaptation for Pre-trained Vision Transformers
CVPR 2025
Subgraph Federated Learning for Local Generalization
ICLR 2025
Subspace Constraint and Contribution Estimation for Heterogeneous Federated Learning
CVPR 2025
Tackling Intertwined Data and Device Heterogeneities in Federated Learning with Unlimited Staleness
AAAI 2025
Task-Aware Prompt Gradient Projection for Parameter-Efficient Tuning Federated Class-Incremental Learning
ICCV 2025
Tensor-aggregated LoRA in Federated Fine-tuning
ICCV 2025
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond
JMLR 2025
Towards Faster Decentralized Stochastic Optimization with Communication Compression
ICLR 2025
Towards Federated Low-Rank Adaptation of Language Models with Rank Heterogeneity
NAACL 2025
Towards Federated RLHF with Aggregated Client Preference for LLMs
ICLR 2025
Towards Robust and Efficient Federated Low-Rank Adaptation with Heterogeneous Clients
ACL 2025
Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning
ICLR 2025
TRAIL: Trust-Aware Client Scheduling for Semi-Decentralized Federated Learning
AAAI 2025
TTA-FedDG: Leveraging Test-Time Adaptation to Address Federated Domain Generalization
AAAI 2025