AI RESEARCH
ZEBRA: Zero-shot Budgeted Resource Allocation for LLM Orchestration
arXiv CS.LG
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ArXi:2605.20485v1 Announce Type: new As autonomous agents increasingly execute end-to-end tasks under fixed monetary budgets, the pressing open question shifts from whether the budget is respected, to how to spend it effectively. Existing budget-aware methods typically control reasoning step-by-step within a single agent, or learn resource allocation policies via RL. None address how to split a budget across the composing phases of a multi-agent pipeline at inference time.