activity
20142026
most citedLarge Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection

3 citations · 6 across the 11 of their papers we have counts for

collaborators
Showing 2024Show all

5 papers · 1 filter

eess.SP2024

Hardware Limitations of Dynamic Metasurface Antennas in the Uplink: A Comparative Study

Maryam Rezvani, Raviraj Adve, Amr El-Keyi +1

Dynamic Metasurface Antennas (DMAs) have emerged as promising candidates for basestation deployment in the next generation of wireless communications. While overlooking the practic…

eess.SP2024★ 1 cited

Uplink Wave-Domain Combiner for Stacked Intelligent Metasurfaces Accounting for Hardware Limitations

Maryam Rezvani, Raviraj Adve, Akram bin Sediq +1

Refractive metasurfaces (RMTSs) offer a promising solution to improve energy efficiency of wireless systems. To address the limitations of single-layer RMTS, stacked intelligent me…

cs.LG2024★ 1 cited

Generative AI-in-the-loop: Integrating LLMs and GPTs into the Next Generation Networks

Han Zhang, Akram Bin Sediq, Ali Afana +1

In recent years, machine learning (ML) techniques have created numerous opportunities for intelligent mobile networks and have accelerated the automation of network operations. How…

cs.CV2024

Generative AI Empowered LiDAR Point Cloud Generation with Multimodal Transformer

Mohammad Farzanullah, Han Zhang, Akram Bin Sediq +2

Integrated sensing and communications is a key enabler for the 6G wireless communication systems. The multiple sensing modalities will allow the base station to have a more accurat…

cs.LG2024★ 3 cited

Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection

Han Zhang, Akram Bin Sediq, Ali Afana +1

Large language models (LLMs), especially generative pre-trained transformers (GPTs), have recently demonstrated outstanding ability in information comprehension and problem-solving…