English

Latent Space Alignment for Semantic Channel Equalization

Machine Learning 2024-06-05 v2 Computation and Language Information Theory math.IT

Abstract

We relax the constraint of a shared language between agents in a semantic and goal-oriented communication system to explore the effect of language mismatch in distributed task solving. We propose a mathematical framework, which provides a modelling and a measure of the semantic distortion introduced in the communication when agents use distinct languages. We then propose a new approach to semantic channel equalization with proven effectiveness through numerical evaluations.

Keywords

Cite

@article{arxiv.2405.13511,
  title  = {Latent Space Alignment for Semantic Channel Equalization},
  author = {Tomás Hüttebräucker and Mohamed Sana and Emilio Calvanese Strinati},
  journal= {arXiv preprint arXiv:2405.13511},
  year   = {2024}
}

Comments

Accepted for publication at 2024 IEEE ICMLCN

R2 v1 2026-06-28T16:35:30.558Z