3 citations · 3 across the 9 of their papers we have counts for
9 papers
Uncertainty Signals for Network Intent Translation: Risk Ranking and Ambiguity Localization
Ala' A. Alsamarneh, Omar Alhussein
Intent-based networking realization starts by translating high-level intents into low-level network configurations. Recent approaches have shifted toward LLM-based translation. Des…
Index-Free Dynamic Edge Retrieval with Energy-Tail-Aware Partial Scans
Mohammad Arif Rasyidi, Omar Alhussein
Dynamic maximum inner-product search (MIPS) returns the stored vectors with the largest dot products with a query while allowing the dataset to change through insertions, repla…
LLM-Aided A* Search in Non-Geometric Network Graphs
Nouf Alabbasi, Esraa Ghourab, Omar Alhussein
Finding the shortest path in non-geometric network graphs, where edge weights encode arbitrary metrics such as latency or monetary cost rather than spatial distance, poses a challe…
LLM-Enabled NWDAF: A Step Toward AI-Native 6G Network Intelligence
Henok Daniel, Omar Alhussein, Cheng Li +2
The Network Data Analytics Function (NWDAF) is central to enabling zero-touch network management in fifth-generation (5G) networks by supporting real-time analytics and closed-loop…
Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge
Omar Erak, Omar Alhussein, Hatem Abou-Zeid +2
Large-scale transformers are central to modern semantic communication, yet their high computational and communication costs hinder deployment on resource-constrained edge devices.…
Adaptive Pareto-Optimal Token Merging for Edge Transformer Models in Semantic Communication
Omar Erak, Omar Alhussein, Hatem Abou-Zeid +1
Large-scale transformer models have emerged as a powerful tool for semantic communication systems, enabling edge devices to extract rich representations for robust inference across…
Rethinking Strategic Mechanism Design In The Age Of Large Language Models: New Directions For Communication Systems
Ismail Lotfi, Nouf Alabbasi, Omar Alhussein
This paper explores the application of large language models (LLMs) in designing strategic mechanisms -- including auctions, contracts, and games -- for specific purposes in commun…
Contrastive Learning and Adversarial Disentanglement for Privacy-Aware Task-Oriented Semantic Communication
Omar Erak, Omar Alhussein, Wen Tong
Task-oriented semantic communication systems have emerged as a promising approach to achieving efficient and intelligent data transmission in next-generation networks, where only i…
Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standards
Omar Erak, Nouf Alabbasi, Omar Alhussein +4
Recent studies show that large language models (LLMs) struggle with technical standards in telecommunications. We propose a fine-tuned retrieval-augmented generation (RAG) system b…