OptArgus deploys a conductor-plus-specialist multi-agent architecture and a new four-category hallucination taxonomy to detect structural errors in LLM-generated optimization models more reliably than single-agent baselines on a three-part benchmark.
Missing`x <= U`,`x >= L`, start-of-horizon, or end-of-horizon conditions should not be labeled as a generic business rule
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OptArgus: A Multi-Agent System to Detect Hallucinations in LLM-based Optimization Modeling
OptArgus deploys a conductor-plus-specialist multi-agent architecture and a new four-category hallucination taxonomy to detect structural errors in LLM-generated optimization models more reliably than single-agent baselines on a three-part benchmark.