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AGAO combines three components: (1) goal-aware attention, measuring semantic relevance between user goals and agent capabiliti","title":"Focus Is All You Need: Adaptive Goal-aware Attention Orchestration for Multi-Agent Graph Systems","url":"https://arxiv.org/abs/2607.23678","vendor":"arxiv_cs_ai"},"summary":"arXiv:2607.23678v1 Announce Type: new \nAbstract: Large language models (LLMs) enable autonomous agents for reasoning, planning, and tool use. Recent systems increasingly organize these agents as graphs of specialized, interconnected nodes. Although graph-based orchestration supports flexible decomposition and coordination, it creates a key challenge: \\textbf{attention allocation}. As workflows grow, existing approaches often execute graph components uniformly, wasting resources on irrelevant or low-impact tasks. We introduce \\textbf{Attention Orchestration}, a paradigm that extends Transformer-style attention from token representations to workflow-level agent coordination. 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