14 citations · 35 across the 12 of their papers we have counts for
12 papers
Telco-oRAG: Optimizing Retrieval-augmented Generation for Telecom Queries via Hybrid Retrieval and Neural Routing
Andrei-Laurentiu Bornea, Fadhel Ayed, Antonio De Domenico +3
Artificial intelligence will be one of the key pillars of the next generation of mobile networks (6G), as it is expected to provide novel added-value services and improve network p…
Age of Information Optimization with Preemption Strategies for Correlated Systems
Egemen Erbayat, Ali Maatouk, Peng Zou +1
In this paper, we examine a multi-sensor system where each sensor monitors multiple dynamic information processes and transmits updates over a shared communication channel. These u…
Hermes: A Large Language Model Framework on the Journey to Autonomous Networks
Fadhel Ayed, Ali Maatouk, Nicola Piovesan +3
The drive toward automating cellular network operations has grown with the increasing complexity of these systems. Despite advancements, full autonomy currently remains out of reac…
Pay Attention to What Matters
Pedro Luiz Silva, Antonio de Domenico, Ali Maatouk +1
Despite the remarkable success of Large Language Models (LLMs), they still exhibit a limited capability to align their outputs to the user instructions. In this work, we introduce…
Telco-RAG: Navigating the Challenges of Retrieval-Augmented Language Models for Telecommunications
Andrei-Laurentiu Bornea, Fadhel Ayed, Antonio De Domenico +2
The application of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems in the telecommunication domain presents unique challenges, primarily due to the co…
Age of Information Optimization and State Error Analysis for Correlated Multi-Process Multi-Sensor Systems
Egemen Erbayat, Ali Maatouk, Peng Zou +1
In this paper, we examine a multi-sensor system where each sensor may monitor more than one time-varying information process and send status updates to a remote monitor over a comm…
FlexTrain: A Dynamic Training Framework for Heterogeneous Devices Environments
Mert Unsal, Ali Maatouk, Antonio De Domenico +2
As deep learning models become increasingly large, they pose significant challenges in heterogeneous devices environments. The size of deep learning models makes it difficult to de…
TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge
Ali Maatouk, Fadhel Ayed, Nicola Piovesan +3
We introduce TeleQnA, the first benchmark dataset designed to evaluate the knowledge of Large Language Models (LLMs) in telecommunications. Comprising 10,000 questions and answers,…
Large Language Models for Telecom: Forthcoming Impact on the Industry
Ali Maatouk, Nicola Piovesan, Fadhel Ayed +2
Large Language Models (LLMs), AI-driven models that can achieve general-purpose language understanding and generation, have emerged as a transformative force, revolutionizing field…
How Costly Was That (In)Decision?
Peng Zou, Ali Maatouk, Jin Zhang +1
In this paper, we introduce a new metric, named Penalty upon Decision (PuD), for measuring the impact of communication delays and state changes at the source on a remote decision m…
An Optimization Framework For Anomaly Detection Scores Refinement With Side Information
Ali Maatouk, Fadhel Ayed, Wenjie Li +3
This paper considers an anomaly detection problem in which a detection algorithm assigns anomaly scores to multi-dimensional data points, such as cellular networks' Key Performance…
A Framework for the Evaluation of Network Reliability Under Periodic Demand
Ali Maatouk, Fadhel Ayed, Shi Biao +3
In this paper, we study network reliability in relation to a periodic time-dependent utility function that reflects the system's functional performance. When an anomaly occurs, the…