Right Answers, Costly Models: The Efficiency Gap in LLM-based Optimization Modeling
cs.LG, cs.AI
Submitted: 2026-09-30
Updated: 2026-09-30
Code: https://github.com/ZhongLIFR/EfficientOpt
Sources
- FrontierOR: Benchmarking LLMs' Capacity for Efficient Algorithm Design in Large-Scale Optimization
- OptArgus: A Multi-Agent System to Detect Hallucinations in LLM-based Optimization Modeling
- MM-OptBench: A Solver-Grounded Benchmark for Multimodal Optimization Modeling
- PEARL: Solver-in-the-Loop Interactive Optimization Modeling from Natural Language
- Formalize, Don't Optimize: The Heuristic Trap in LLM-Generated Combinatorial Solvers
- ORGEval: Graph-Theoretic Evaluation of LLMs in Optimization Modeling
- A Survey of Optimization Modeling Meets LLMs: Progress and Future Directions
- OptSkills: Learning Generalizable Optimization Skills from Problem Archetypes via Cluster-Based Distillation
- OptiMind: Teaching LLMs to Think Like Optimization Experts
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