2 citations · 3 across the 8 of their papers we have counts for
6 papers · 1 filter
Application-Integrated Slicing towards 6G: The Musical Metaverse Use Case
Ali Al Housseini, Jaime Llorca, Omran Ayoub +3
Emerging immersive applications are expected to support heterogeneous groups of users with fundamentally different communication and computation requirements. Using the Musical Met…
Cross-Domain Generalization in Optical Networks via Joint Contrastive and Classification Learning
Ali Al Housseini, Carlos Natalino, Paolo Monti +1
The robustness of machine learning techniques across heterogeneous network domains remains an open challenge in optical networks. Models trained on data from a specific topology or…
Human Grounded Evaluation of Large Language Models for Optical Network Automation
Kiarash Rezaei, Omran Ayoub, Paolo Monti +1
Large language models (LLMs) are increasingly adopted for network automation, yet their output quality and inference cost can vary substantially across LLM families. We present HuG…
Generative Explainability for Next-Generation Networks: LLM-Augmented XAI with Mutual Feature Interactions
Kiarash Rezaei, Omran Ayoub, Sebastian Troia +3
As artificial intelligence and machine learning (AI/ML) models become integral to network operations, their lack of transparency poses a significant barrier to operator trust. Exis…
MuMeNet: A Network Simulator for Musical Metaverse Communications
Ali Al Housseini, Jaime Llorca, Luca Turchet +3
The Metaverse, a shared and spatially organized digital continuum, is transforming various industries, with music emerging as a leading use case. Live concerts, collaborative compo…
Exploiting the Alternatives: Coordinated Learning via Hierarchical RL for Dynamic VNEAP
Ali Al Housseini, Cristina Rottondi, Sebastian Troia +1
Virtual Network Embedding (VNE) is a key enabler of network slicing, yet most formulations assume that each Virtual Network Request (VNR) has a fixed topology. Recently, VNE with A…