20 citations · 26 across the 9 of their papers we have counts for
16 papers
Relative Representations of Latent Spaces enable Efficient Semantic Channel Equalization
Tomás Hüttebräucker, Simone Fiorellino, Mohamed Sana +2
In multi-user semantic communication, language mismatche poses a significant challenge when independently trained agents interact. We present a novel semantic equalization algorith…
Semantic Communication Enhanced by Knowledge Graph Representation Learning
Nour Hello, Paolo Di Lorenzo, Emilio Calvanese Strinati
This paper investigates the advantages of representing and processing semantic knowledge extracted into graphs within the emerging paradigm of semantic communications. The proposed…
Adaptive Semantic Token Selection for AI-native Goal-oriented Communications
Alessio Devoto, Simone Petruzzi, Jary Pomponi +2
In this paper, we propose a novel design for AI-native goal-oriented communications, exploiting transformer neural networks under dynamic inference constraints on bandwidth and com…
Opportunistic Information-Bottleneck for Goal-oriented Feature Extraction and Communication
Francesco Binucci, Paolo Banelli, Paolo Di Lorenzo +1
The Information Bottleneck (IB) method is an information theoretical framework to design a parsimonious and tunable feature-extraction mechanism, such that the extracted features a…
Goal-Oriented and Semantic Communication in 6G AI-Native Networks: The 6G-GOALS Approach
Emilio Calvanese Strinati, Paolo Di Lorenzo, Vincenzo Sciancalepore +17
Recent advances in AI technologies have notably expanded device intelligence, fostering federation and cooperation among distributed AI agents. These advancements impose new requir…
Enabling Edge Artificial Intelligence via Goal-oriented Deep Neural Network Splitting
Francesco Binucci, Mattia Merluzzi, Paolo Banelli +2
Deep Neural Network (DNN) splitting is one of the key enablers of edge Artificial Intelligence (AI), as it allows end users to pre-process data and offload part of the computationa…