Newest papers

ORSMT: Unleashing the Potential of Satisfiability Modulo Theories for Semantic Verification and Repair in LLM-Based Optimization

Rui Zhang, Chenyu Zhou, Jianghao Lin, Yaoxin Wu, Dongdong Ge, 宋文 · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.29145 · cited by 0 works (OpenAlex) · open-access PDF

Japanese

大規模な言語モデルは、自然言語の問題から最適化モデリングをますます自動化し、書かれた数学、ソーラーコードと返されたレポートを生成します。これらのアーティファクトを通じて1つの最適化問題を検証するには、セマンティックな比較が必要です:不平等なモデルは同じ目標を達成することができ、同等なモデルは異なる補助変数を使用することができ、相互に一致したアーティファクトは同じソース要件を省略することがあります。 ORSMTは別のアーティファクトを構築し、正確なSMT関係クエリを提供します。それは観察可能な決定、プロジェクトの補助変数を調節し、実行可能な領域と客観的な関係を証明または否定し、含まれる行

Machine translation (Meta M2M100); the English original follows.

Abstract

Large language models increasingly automate optimization modeling from natural language problems, producing written mathematics, solver code and a returned report. Verifying one optimization problem across these artifacts requires semantic comparison: unequal models can attain the same objective, equivalent models can use different auxiliary variables, and mutually consistent artifacts can omit the same source requirement. ORSMT provides a typed semantic interface and exact SMT relation queries. It aligns observable decisions, projects auxiliary variables, proves or refutes feasible region and objective relations, localizes refutations to implicated rows or domains and links source texts when available. It then reconstructs one artifact from another, and each adopted candidate passes the required relation checks. Across 3,034 problems and six generator sizes, ORSMT improves the model-code match rate in all 72 benchmark and generator combinations before selection. Protected selection raises the aggregate rate from 43.2% to 88.2% and the share that are both correct and matched from 25.2% to 40.2%. On the 1,905 refuted outputs, certified voting under the shared fallback makes 50.9% of outputs correct and matched, compared with 44.8% for ReLoop and 49.4% for Opt-Verifier. A separate one-round source revision followed by exact reconstruction restores a model-code match for 84.4% of the refuted pairs.

Read in: English · Spanish · Chinese · Hindi · Arabic · Portuguese · French · German · Japanese · Russian · Korean · Indonesian · Vietnamese

Topics: Computer science, Artifact (error), Generator (circuit theory), Satisfiability modulo theories, Solver, Theoretical computer science

Sources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange