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20242026
most citedMulti-Modal Federated Learning for Cancer Staging over Non-IID Datasets with Unbalanced Modalities

22 citations · 26 across the 8 of their papers we have counts for

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6 papers · 1 filter

cs.LG2025★ 2 cited

Bringing Multi-Modal Multi-Task Federated Foundation Models to Education Domain: Prospects and Challenges

Kasra Borazjani, Naji Khosravan, Rajeev Sahay +2

Multi-modal multi-task (M3T) foundation models (FMs) have recently shown transformative potential in artificial intelligence, with emerging applications in education. However, thei…

cs.LG2025

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…

cs.LG2025★ 1 cited

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…

cs.AI2025

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…

cs.CV2025★ 1 cited

Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels to Embeddings for Task-Specific Data Distributions

Kasra Borazjani, Payam Abdisarabshali, Naji Khosravan +1

Federated Learning (FL) has emerged as one of the prominent paradigms for distributed machine learning (ML). However, it is well-established that its performance can degrade signif…

eess.SP2025

FLAME: A Federated Learning Approach for Multi-Modal RF Fingerprinting

Kasra Borazjani, Kiarash Kianfar, Seyyedali Hosseinalipour +1

Authorization systems are increasingly relying on processing radio frequency (RF) waveforms at receivers to fingerprint (i.e., determine the identity of) the corresponding transmit…