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Cooperative Multi-Task Semantic Communication for Joint Classification and Regression Tasks
Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accurate reconstruction in future intelligent networks. In our prior work [1], we introduced the cooperative multi-task SemCom (CMT-SemCom) framework, in which the semantic encoder is divided into a common unit (CU) and multiple specific units (SUs) to facilitate cooperative multi-task processing. However, CMT-SemCom has been evaluated on homogeneous classification tasks on simplistic datasets, limiting its applicability to real-world perception systems. In this paper, we extend our CMT-Sem
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-03T15:13:25.000Z
First collected: 2026-09-21T04:51:57.792Z. This is not the publication date.