5 papers
Kafila: Serving Large Language Models on a Trusted Set of Heterogeneous Commodity Machines
Murtaza Rangwala, Richard O. Sinnott, Rajkumar Buyya
Between them, the members of a research group or a circle of friends own several consumer computers, none large enough to run a capable large language model. Existing systems pool…
Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking
Shuzhi Gong, Richard O. Sinnott, Jianzhong Qi +3
Misinformation spreading over the Internet poses a significant threat to both societies and individuals, necessitating robust and scalable fact-checking that relies on retrieving a…
Evidential Trust-Aware Model Personalization in Decentralized Federated Learning for Wearable IoT
Murtaza Rangwala, Richard O. Sinnott, Rajkumar Buyya
Decentralized federated learning (DFL) enables collaborative model training across edge devices without centralized coordination, offering resilience against single points of failu…
Screen Before You Fetch: Compressed Byzantine Screening for Decentralized Learning on the Edge-Cloud Continuum
Murtaza Rangwala, Farag Azzedin, Richard O. Sinnott +1
In decentralized federated learning, Byzantine-robust defenses filter neighbors by model similarity, but only after receiving each neighbor's full model. On constrained edge uplink…
Topology-Aware Differential Privacy in Hierarchical Federated Learning
Murtaza Rangwala, Richard O. Sinnott, Rajkumar Buyya
Hierarchical federated learning places regional aggregators between clients and the cloud, so a participant's update is observed only alongside its neighbours'. The concealment thi…