Forgetting to Witness: Efficient Federated Unlearning and Its Visible Evaluation

ArXi:2604.04800v1 Announce Type: new With the increasing importance of data privacy and security, federated unlearning has emerged as a novel research field dedicated to ensuring that federated learning models no longer retain or leak relevant information once specific data has been deleted. In this paper, to the best of our knowledge, we propose the first complete pipeline for federated unlearning, which includes a federated unlearning approach and an evaluation framework.