3 papers
cs.CR2026
Model Multiplicity for Adversarial Detection in Small Language Model Training on Edge Devices
Stefan Behfar, Richard Mortier
The rise of edge-based machine learning has enabled distributed adaptation of language models across mobile and IoT devices, offering privacy preservation and real-time responsiven…
cs.DC2026
Robust Synchronisation for Federated Learning in The Face of Correlated Device Failure
Stefan Behfar, Richard Mortier
Probabilistic Synchronous Parallel (PSP) is a technique in distributed learning systems to reduce synchronization bottlenecks by sampling a subset of participating nodes per round.…
cs.LG2026
Cumulative Utility Parity for Fair Federated Learning under Intermittent Client Participation
Stefan Behfar, Richard Mortier
In real-world federated learning (FL) systems, client participation is intermittent, heterogeneous, and often correlated with data characteristics or resource constraints. Existing…