Adaptive Semantic Token Communication for Transformer-Based Edge Inference

This paper presents an adaptive framework for edge inference based on a dynamically configurable transformer-powered deep joint source channel coding (DJSCC) architecture. Motivated by a practical scenario where a resource constrained edge device engages in goal oriented semantic communication, such...

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Autors principals:	Alessio Devoto, Jary Pomponi, Mattia Merluzzi, Paolo Di Lorenzo, Simone Scardapane
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2026-01-01
Col·lecció:	IEEE Transactions on Machine Learning in Communications and Networking
Matèries:	Semantic communications goal-oriented communications deep joint source channel coding token communications edge inference transformers
Accés en línia:	https://ieeexplore.ieee.org/document/11369909/
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