Coupled Hierarchical Search over Topology and Execution for Agentic Workflow Synthesis
Although structured workflows empower Large Language Models (LLMs) to tackle complex problems, automating their creation is severely hindered by a vast combinatorial search space, frequently resulting in inflexible and resource-heavy offline training dependencies. To address this, we conceptualize workflow generation as an intertwined topology-and-execution search paradigm, where the broader topological layer dictates subtask boundaries and lower-level execution outcomes actively reshape the topology itself. Building on this foundation, we introduce HierFlow, a training-free, test-time hierarchical search architecture that automates agentic workflow design by merging feedback-guided topol...
| Authors | Dong Li, Yanchi Liu, Xujiang Zhao et al. |
|---|---|
| Primary category | cs.AI |
| Published | 20 May 2026 |
| Last updated at source | 20 May 2026 |
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