Latent Space Alignment for Semantic Channel Equalization
Fuente:
arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866929372792881152 |
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| author | Hüttebräucker, Tomás Sana, Mohamed Strinati, Emilio Calvanese |
| author_facet | Hüttebräucker, Tomás Sana, Mohamed Strinati, Emilio Calvanese |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_13511 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Latent Space Alignment for Semantic Channel Equalization Hüttebräucker, Tomás Sana, Mohamed Strinati, Emilio Calvanese Machine Learning Computation and Language Information Theory 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. |
| title | Latent Space Alignment for Semantic Channel Equalization |
| topic | Machine Learning Computation and Language Information Theory |
| url | https://arxiv.org/abs/2405.13511 |