Truthful and Expected-Payment-Optimal Model Routing in Graph-Based Agentic Workflows
Assigning routine tasks to cheaper large language model (LLM) providers can reduce generation cost, but switching providers may require processing accumulated context again. Keeping dependent tasks with the same provider can instead reuse eligible context. Graph-based workflows therefore couple routing decisions across tasks. Independent providers may also privately know their real-time unit costs and strategically misreport them. We formulate this routing problem as a single-parameter procurement auction and propose STAR (Strategy-proof Topology-aware Agent Routing), which minimizes virtual-cost-weighted graph workloads. Its allocation rule and payments, computed by integrating workload ...
| Authors | Jiayuan Liu, Mingyu Guo, Jiarui Gan et al. |
|---|---|
| Primary category | cs.GT |
| Published | 13 October 2026 |
| Last updated at source | 13 October 2026 |
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