Helicase: Uncertainty-Guided Supply Chain Knowledge Graph Construction with Autonomous Multi-Agent LLMs
The article introduces Helicase, an autonomous multi-agent LLM system designed for constructing supply chain knowledge graphs. It addresses the challenges of multi-hop reasoning and uncertainty in information retrieval. The system aims to improve decision-making by providing calibrated confidence in the reliability of synthesized information.
- ▪Helicase decomposes complex supply chain queries into executable investigation plans.
- ▪It coordinates specialized agents for web search, reasoning, and coding through iterative verification loops.
- ▪The system includes a three-layer uncertainty framework to track uncertainty at various levels.
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Computer Science > Artificial Intelligence arXiv:2605.26835 (cs) [Submitted on 26 May 2026] Title:Helicase: Uncertainty-Guided Supply Chain Knowledge Graph Construction with Autonomous Multi-Agent LLMs Authors:Yunbo Long, Haolang Zhao, Ge Zheng, Alexandra Brintrup View a PDF of the paper titled Helicase: Uncertainty-Guided Supply Chain Knowledge Graph Construction with Autonomous Multi-Agent LLMs, by Yunbo Long and 3 other authors View PDF HTML (experimental) Abstract:LLM-based multi-agent systems have been widely adopted for knowledge retrieval and report generation, synthesizing known information through web search and textual reasoning.
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