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cs.IT2026

Compositional Semantic Communication for Physical AI: Category Theory Meets Game Theory

Christo Kurisummoottil Thomas, Walid Saad, Emilio Calvanese Strinati

Physical artificial intelligence (AI) systems involve distributed sensing agents with embedded AI models that must coordinate to perceive, reason, and act in networked environments…

cs.IT2026

Resilience Characterization of AI-Native Wireless Receivers via Persistent Homology

Christo Kurisummoottil Thomas, Emilio Calvanese Strinati

AI-native wireless receivers based on deep learning exhibit remarkable performance under stationary channel conditions, yet their resilience to distributional shifts remains poorly…

cs.IT2026

Distributed Semantic Alignment over Interference Channels: A Game-Theoretic Approach

Giuseppe Di Poce, Mattia Merluzzi, Emilio Calvanese Strinati +1

Semantic communication acts as a key enabler for effective task execution in AI-driven systems, prioritizing the extraction of the underlying meaning before transmission. However,…

cs.IT2026

Federated Latent Space Alignment for Multi-user Semantic Communications

Giuseppe Di Poce, Mario Edoardo Pandolfo, Emilio Calvanese Strinati +1

Semantic communication aims to convey meaning for effective task execution, but differing latent representations in AI-native devices can cause semantic mismatches that hinder mutu…

cs.IT2025

Collaborative Edge Inference via Semantic Grouping under Wireless Channel Constraints

Mateus P. Mota, Mattia Merluzzi, Emilio Calvanese Strinati

In this paper, we study the framework of collaborative inference, or edge ensembles. This framework enables multiple edge devices to improve classification accuracy by exchanging i…

cs.IT2025

Joint Channel and Semantic-aware Grouping for Effective Collaborative Edge Inference

Mateus P. Mota, Mattia Merluzzi, Emilio Calvanese Strinati

We focus on collaborative edge inference over wireless, which enables multiple devices to cooperate to improve inference performance in the presence of corrupted data. Exploiting a…