SDOF: Taming the Alignment Tax in Multi-Agent Orchestration with State-Constrained Dispatch
The article discusses the SDOF framework designed to enhance multi-agent orchestration by enforcing state constraints. It highlights the framework's components, including an intent router and a dispatcher, which improve task completion rates and accuracy. The results indicate that SDOF outperforms existing models in specific benchmarks and provides robust execution control.
- ▪SDOF treats multi-agent execution as a constrained state machine.
- ▪The framework includes an Online-RLHF Specialized Intent Router and a StateAwareDispatcher.
- ▪In a recruitment system, SDOF achieved 86.5% task completion and blocked all operations in the illegal HR subset.
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Computer Science > Artificial Intelligence arXiv:2605.15204 (cs) [Submitted on 20 Apr 2026] Title:SDOF: Taming the Alignment Tax in Multi-Agent Orchestration with State-Constrained Dispatch Authors:Zhantao Wang View a PDF of the paper titled SDOF: Taming the Alignment Tax in Multi-Agent Orchestration with State-Constrained Dispatch, by Zhantao Wang View PDF HTML (experimental) Abstract:Multi-agent orchestration frameworks such as LangChain, LangGraph, and CrewAI route tasks through graph-based pipelines but do not enforce the stage constraints that govern real business processes. We present SDOF, a framework that treats multi-agent execution as a constrained state machine.
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