SemOPT: Fixing Semantic Errors in LLM-based Optimization Modeling via Reward-Guided Search

arXiv:2609.37361 · cs.CL · Submitted 2026-09-29 · Read on arXiv

cs.CL

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• Accuracy — 34× in this paper · explained in 1 episode
• Benchmark — 22× in this paper · explained in 2 episodes
• Consistency — 6× in this paper · explained in 3 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Fine-Tuning — 5× in this paper · explained in 5 episodes
• Objective Function — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• AUC — 2× in this paper · explained in 2 episodes
• Abstraction — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Naive Search — 2× in this paper
• Robustness — 2× in this paper · explained in 5 episodes
• Semantic Alignment — 2× in this paper · explained in 3 episodes
• Beam Search — 1× in this paper
• Benchmarking — 1× in this paper · explained in 3 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Error Localization — 1× in this paper · explained in 2 episodes
• Error Taxonomy — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Multi-Agent Framework — 1× in this paper · explained in 3 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Test-time Scaling — 1× in this paper · explained in 2 episodes
• Verifiable Rewards — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scale
• A Semantic-based Optimization Approach for Repairing LLMs: Case Study on Code Generation
• Enhancing Source Code Security with LLMs: Demystifying The Challenges and Generating Reliable Repairs
• Qwen3 Technical Report
• SAC-Opt: Semantic Anchors for Iterative Correction in Optimization Modeling

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