AI & ML
Receiver-Specific Interventional Valuation of Semantic Atoms for Budget-Constrained Multi-Agent Communication
arXiv eess.SP0 views
arXiv:2610.21504v1 Announce Type: new Abstract: Cooperative multi-agent semantic communication requires deciding not only how a transmitter encodes its observation, but also which resulting semantic content should be delivered to each receiver under a limited link budget. We introduce an encoder-agnostic transmitter-side framework for receiver-specific valuation of independently selectable semantic units, termed semantic atoms. Each atom is assigned a signed value that quantifies whether delivering it is expected to improve or degrade the intended receiver's downstream decision. We formulate this effect through a controlled-delivery utility and identify it via prospective randomized payload delivery before the receiver acts. A shadow receiver estimates this utility using only transmitter-available information, from which receiver-specific leave-one-out (LOO) and Shapley atom values are computed. Experiments on a four-receiver intersection benchmark show 68.4% accuracy in recovering the sign of non-negligible LOO atom effects and a Spearman correlation of 0.302 between estimated and reference LOO values. Under limited budgets, we show that receiver-specific selection consistently outperforms shared and random alternatives, demonstrating the benefit of adapting semantic ranking to the intended receiver. At full affordability, exhaustive subset selection also outperforms full-payload transmission, showing that transmitting all available content need not maximize receiver utility. Overall, our results show that receiver-specific semantic valuation can support effective budget-constrained communication despite imperfect atom-value estimation.
Source:https://arxiv.org/abs/2610.21504PreviousMicro-Doppler Sensing for UAV Flight-State Estimation in ISAC NetworksNextWavefront Engineering for Physical Layer Security in Near-Field Wireless Communications
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