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Research questionHow can an LLM decide when to ask clarifying questions before formulating an optimization model?Natural-language optimization requests may omit objectives, constraints, or business rules, and each omission can change the resulting mathematical program. The agent must balance obtaining a sufficient specification against unnecessary interaction and unsupported assumptions.
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Latest papersRecent research connected to this question, newest first.Ask Before You Optimize: Dynamic Pre-Formulation Clarification for Interactive OptimizationThe evidence concerns LLM agents interacting with a simulated user under bounded interaction, using open-ended or choice-based clarification. It measures slot recovery, stopping behavior, silent assumptions, and interaction cost, including a proposed two-stage framework; it does not establish performance in live-user deployments.research paper · Sep 8, 2026
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