3 papers
cs.CL2025
Explaining Matters: Leveraging Definitions and Semantic Expansion for Sexism Detection
Sahrish Khan, Arshad Jhumka, Gabriele Pergola
The detection of sexism in online content remains an open problem, as harmful language disproportionately affects women and marginalized groups. While automated systems for sexism…
cs.LG2025
FlexFed: Mitigating Catastrophic Forgetting in Heterogeneous Federated Learning in Pervasive Computing Environments
Sara Alosaime, Arshad Jhumka
Federated Learning (FL) enables collaborative model training while preserving privacy by allowing clients to share model updates instead of raw data. Pervasive computing environmen…
cs.LG2025
RIFLES: Resource-effIcient Federated LEarning via Scheduling
Sara Alosaime, Arshad Jhumka
Federated Learning (FL) is a privacy-preserving machine learning technique that allows decentralized collaborative model training across a set of distributed clients, by avoiding r…