most citedFedBAP: Backdoor Defense via Benign Adversarial Perturbation in Federated Learning

2 citations · 2 across the 1 of their papers we have counts for

collaborators

2 papers

cs.CR2025★ 2 cited

FedBAP: Backdoor Defense via Benign Adversarial Perturbation in Federated Learning

Xinhai Yan, Libing Wu, Zhuangzhuang Zhang +3

Federated Learning (FL) enables collaborative model training while preserving data privacy, but it is highly vulnerable to backdoor attacks. Most existing defense methods in FL hav…

cs.CV2025

mmCooper: A Multi-agent Multi-stage Communication-efficient and Collaboration-robust Cooperative Perception Framework

Bingyi Liu, Jian Teng, Hongfei Xue +4

Collaborative perception significantly enhances individual vehicle perception performance through the exchange of sensory information among agents. However, real-world deployment f…