6 citations · 6 across the 4 of their papers we have counts for
4 papers
LLM-Enabled In-Context Learning for Data Collection Scheduling in UAV-assisted Sensor Networks
Yousef Emami, Hao Zhou, SeyedSina Nabavirazani +1
Unmanned Aerial Vehicles (UAVs) are increasingly being utilized in various private and commercial applications, e.g., traffic control, parcel delivery, and Search and Rescue (SAR)…
Distributed LLMs and Multimodal Large Language Models: A Survey on Advances, Challenges, and Future Directions
Hadi Amini, Md Jueal Mia, Yasaman Saadati +6
Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as tex…
Do We Really Need to Design New Byzantine-robust Aggregation Rules?
Minghong Fang, Seyedsina Nabavirazavi, Zhuqing Liu +3
Federated learning (FL) allows multiple clients to collaboratively train a global machine learning model through a server, without exchanging their private training data. However,…
LAKEE: A Lightweight Authenticated Key Exchange Protocol for Power Constrained Devices
Seyedsina Nabavirazavi, S. Sitharama Iyengar
The rapid development of IoT networks has led to a research trend in designing effective security features for them. Due to the power-constrained nature of IoT devices, the securit…