3 papers
cs.AI2026
MoE Router-Guided Clustering for Heterogeneous Federated Instruction Tuning
Ankita Sharma, Bahar Farahani, Sanaz Rahimi Moosavi +3
Federated instruction fine-tuning enables Large Language Models (LLMs) to adapt to decentralized, privacy-sensitive data without requiring data sharing. Recent Mixture-of-Experts (…
cs.CR2025
A Lightweight and Secure Deep Learning Model for Privacy-Preserving Federated Learning in Intelligent Enterprises
Reza Fotohi, Fereidoon Shams Aliee, Bahar Farahani
The ever growing Internet of Things (IoT) connections drive a new type of organization, the Intelligent Enterprise. In intelligent enterprises, machine learning based models are ad…
cs.CR2025
Decentralized and Robust Privacy-Preserving Model Using Blockchain-Enabled Federated Deep Learning in Intelligent Enterprises
Reza Fotohi, Fereidoon Shams Aliee, Bahar Farahani
In Federated Deep Learning (FDL), multiple local enterprises are allowed to train a model jointly. Then, they submit their local updates to the central server, and the server aggre…