1 citations · 1 across the 5 of their papers we have counts for
6 papers
BLEND: Balancing Personalization vs. Generalization in Federated Vision-Language Models
Payam Abdisarabshali, Fardis Nadimi, Kasra Borazjani +3
Federated vision-language models (FedVLMs) represent one of the emerging frontiers of machine learning, aiming to integrate federated learning within the fine-tuning pipelines of v…
Federated Foundation Models over Vehicular Networks
Kasra Borazjani, Fardis Nadimi, Payam Abdisarabshali +5
This paper presents a forward-looking vision for integrating the emerging multi-modal multi-task federated foundation models (M3T FedFMs) into vehicular networks, with the goal of…
Hierarchical Federated Foundation Models over Wireless Networks for Multi-Modal Multi-Task Intelligence: Integration of Edge Learning with D2D/P2P-Enabled Fog Learning Architectures
Payam Abdisarabshali, Fardis Nadimi, Kasra Borazjani +6
The rise of foundation models (FMs) has reshaped the landscape of machine learning. As these models continued to grow, leveraging geo-distributed data from wireless devices has bec…
Graph Theory Meets Federated Learning over Satellite Constellations: Spanning Aggregations, Network Formation, and Performance Optimization
Fardis Nadimi, Payam Abdisarabshali, Jacob Chakareski +2
In this work, we introduce Fed-Span: \textit{\underline{fed}erated learning with \underline{span}ning aggregation over low Earth orbit (LEO) satellite constellations}. Fed-Span aim…
Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR
Fardis Nadimi, Payam Abdisarabshali, Kasra Borazjani +2
Extended reality (XR) systems, which consist of virtual reality (VR), augmented reality (AR), and mixed reality (XR), offer a transformative interface for immersive, multi-modal, a…
Multi-Modal Multi-Task (M3T) Federated Foundation Models for Embodied AI: Potentials and Challenges for Edge Integration
Kasra Borazjani, Payam Abdisarabshali, Fardis Nadimi +5
As embodied AI systems become increasingly multi-modal, personalized, and interactive, they must learn effectively from diverse sensory inputs, adapt continually to user preference…