Papers
FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking
Changlong Shi, Jinmeng Li, He Zhao et al.
FedMABench: Benchmarking Mobile GUI Agents on Decentralized Heterogeneous User Data
WenHao Wang, Zijie Yu, Rui Ye et al.
FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fields
Junhyeog Yun, Minui Hong, Gunhee Kim
FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning
Gongxi Zhu, Donghao Li, Hanlin Gu et al.
FedMKT: Federated Mutual Knowledge Transfer for Large and Small Language Models
Tao Fan, Guoqiang Ma, Yan Kang et al.
FedMSGL: A Self-Expressive Hypergraph Based Federated Multi-View Learning
Daoyuan Li, Zuyuan Yang, Shengli Xie
FedMVP: Federated Multimodal Visual Prompt Tuning for Vision-Language Models
Mainak Singha, Subhankar Roy, Sarthak Mehrotra et al.
FedPall: Prototype-based Adversarial and Collaborative Learning for Federated Learning with Feature Drift
Yong Zhang, Feng Liang, Guanghu Yuan et al.
FedPIA – Permuting and Integrating Adapters Leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning
Pramit Saha, Divyanshu Mishra, Felix Wagner et al.
FedPop: Federated Population-based Hyperparameter Tuning
Haokun Chen, Denis Krompaß, Jindong Gu et al.
FED-PsyAU: Privacy-Preserving Micro-Expression Recognition via Psychological AU Coordination and Dynamic Facial Motion Modeling
Jingting Li, Yu Qian, Lin Zhao et al.
FedSaaS: Class-Consistency Federated Semantic Segmentation via Global Prototype Supervision and Local Adversarial Harmonization
Xiaoyang Yu, Xiaoming Wu, Xin Wang et al.
FedSA: A Unified Representation Learning via Semantic Anchors for Prototype-based Federated Learning
Yanbing Zhou, Xiangmou Qu, Chenlong You et al.
FedSPA: Generalizable Federated Graph Learning under Homophily Heterogeneity
Zihan Tan, Guancheng Wan, Wenke Huang et al.
FedSpaLLM: Federated Pruning of Large Language Models
Guangji Bai, Yijiang Li, Zilinghan Li et al.
FedSPU: Personalized Federated Learning for Resource-Constrained Devices with Stochastic Parameter Update
Ziru Niu, Hai Dong, A. K. Qin
FedSum: Data-Efficient Federated Learning Under Data Scarcity Scenario for Text Summarization
Zhiyong Ma, Zhengping Li, Yuanjie Shi et al.
FedTMOS: Efficient One-Shot Federated Learning with Tsetlin Machine
Shannon How Shi Qi, Jagmohan Chauhan, Geoff V. Merrett et al.
FedVCK: Non-IID Robust and Communication-Efficient Federated Learning via Valuable Condensed Knowledge for Medical Image Analysis
Guochen Yan, Luyuan Xie, Xinyi Gao et al.
FedVLA: Federated Vision-Language-Action Learning with Dual Gating Mixture-of-Experts for Robotic Manipulation
Cui Miao, Tao Chang, Meihan Wu et al.
FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization
Seung-Wook Kim, Seongyeol Kim, Jiah Kim et al.
FedXDS: Leveraging Model Attribution Methods to counteract Data Heterogeneity in Federated Learning
Maximilian Andreas Hoefler, Karsten Mueller, Wojciech Samek
Feedback Favors the Generalization of Neural ODEs
Jindou Jia, Zihan Yang, Meng Wang et al.
Feedback Schrödinger Bridge Matching
Panagiotis Theodoropoulos, Nikolaos Komianos, Vincent Pacelli et al.
FeedEdit: Text-Based Image Editing with Dynamic Feedback Regulation
Fengyi Fu, Lei Zhang, Mengqi Huang et al.