Federated Learning

CO-EVO: Co-evolving Semantic Anchoring and Style Diversification for Federated DG-ReID ACL 2026 DP-FedAdamW: An Efficient Optimizer for Differentially Private Federated Large Models CVPR 2026 Eliminate Distance Differences Induced by Backdoor Attacks: Layer-Selective Training and Clipping to Mask Backdoor Models CVPR 2026 Enhancing Visual Representation with Textual Semantics: Textual Semantics-Powered Prototypes for Heterogeneous Federated Learning CVPR 2026 FedAdamom: Adaptive Momentum for Improved Generalization in Federated Optimization CVPR 2026 FedAlign: Differentially Private Distribution Alignment for Non-IID Federated Learning CVPR 2026 FedARA: Resource-adaptive Low-rank Personalized Federated Learning via Anchor-driven Representation Alignment on Heterogeneous Edge Devices CVPR 2026 FedCART: Tackling Long-Tailed Distributions in Federated Adversarial Training via Classifier Refinement CVPR 2026 Federated Active Learning Under Extreme Non-IID and Global Class Imbalance CVPR 2026 FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion ACL 2026 FedRAC: Rolling Submodel Allocation for Collaborative Fairness in Federated Learning CVPR 2026 FedSDR: Federated Graph Learning with Structural Noise Detection and Reconstruction CVPR 2026 From Selection to Scheduling: Federated Geometry-Aware Correction Makes Exemplar Replay Work Better under Continual Dynamic Heterogeneity CVPR 2026 Guiding Diffusion Models with Fine-Grained Conditions and Semantics-Preserving Sampling for One-Shot Federated Learning CVPR 2026 Heterogeneous Decentralized Diffusion Models CVPR 2026 HFedATM: Hierarchical Federated Domain Generalization via Optimal Transport and Regularized Mean Aggregation CVPR 2026 One-Shot Federated Learning based on Random Feature Extractor UAI 2026 OS-Fed: One Snapshot Is All You Need CVPR 2026 Probabilistic Feature Imputation and Uncertainty-Aware Multimodal Federated Aggregation MIDL 2026 Safe-FedLLM: Delving into the Safety of Federated Large Language Models ACL 2026 Single-Round Scalable Analytic Federated Learning CVPR 2026 Stealing Split Learning Bottom Models by Recovering Embedding Geometry CVPR 2026 Submodel Extraction for Efficient and Personalized Federated Learning via Optimal Transport CVPR 2026 Towards Stable Federated Continual Test-Time Adaptation in Wild World CVPR 2026 Who to Trust? Aggregating Client Predictions in Federated Distillation. UAI 2026