Ask Before You Optimize: Dynamic Pre-Formulation Clarification for Interactive Optimization
- 类型：arxiv
- 标识：2609.05258
- 链接：https://arxiv.org/abs/2609.05258
- 主分类：evaluation
- 形态：benchmark
- TLDR：Large language models (LLMs) are increasingly used to formulate optimization models from natural-language problem descriptions, yet realistic operations research (OR) requests are often incomplete: missing objectives, constraints, or business rules can change the resulting mathematical program. Existing evaluations largely assume a complete specification and therefore overlook whether an agent knows when clarification is needed before modeling. We introduce OR-Clarify, a benchmark for pre-formulation clarification. Each task presents a partial public problem description, withholds structured h
- 待LLM分类：否
- 来源文件：
- /inbox/tom/_candidates/2026-09-07-agent-rag-longcontext-candidates.json