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VQV Signal

RESEARCH SOURCE-BACKED PRACTICAL

Resource-Efficient Semantic Communication for Heterogeneous Agentic Teams

Teams of autonomous agents, including large language model (LLM) agents, must coordinate over scarce and unreliable wireless links. We propose goal-oriented semantic communication (GOSC), a closed-loop co-design that jointly decides what each agent sends, whe...

Source: arXiv · arxiv.org Published 2026-09-30T10:42:39+00:00 Detected 2026-10-01T05:17:44+00:00
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Teams of autonomous agents, including large language model (LLM) agents, must coordinate over scarce and unreliable wireless links. We propose goal-oriented semantic communication (GOSC), a closed-loop co-design that jointly decides what each agent sends, whe...

Teams of autonomous agents, including large language model (LLM) agents, must coordinate over scarce and unreliable wireless links. We propose goal-oriented semantic communication (GOSC), a closed-loop co-design that jointly decides what each agent sends, when it sends it, and how reliably it is transmitted, based...

Signal Strength 95% Technical label SOURCE-BACKED Public Interest 22 Category RESEARCH Reader Depth PRACTICAL

Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.

Public Interest components
Recognizable Entity Score 0 Practical Impact Score 0 Novelty Interest Score 70 Consequence Score 18 Curiosity Score 16 Shareability Score 41

VQV surfaced this signal because it is recent, relevant to AI Agents, connected to arXiv.