arXiv:2605.21751v1 Announce Type: new Abstract: Text-to-optimization requires two separable capabilities: modeling -- choosing the right optimization structure -- and binding -- grounding every coefficient, index, and parameter in the concrete problem data. We study this via Text2Opt-Bench, a scalable benchmark of solver-verified optimization problems spanning 12 categories, from textbook linear programs to stochastic and multi-objective formulations with up to thousands of variables. Across 10+ models, we find that accuracy collapses as instance data grows, even when the formulation itself is
The proliferation of large language models (LLMs) has pushed the boundaries of what AI can achieve, making the limitations in structured grounding a critical bottleneck that new research is now actively addressing.
This research highlights a fundamental challenge in AI's ability to translate high-level understanding into actionable, structured mathematical optimization, directly impacting the deployment of truly autonomous AI agents in complex decision-making scenarios.
The explicit identification and benchmarking of 'binding' as a distinct and challenging capability for AI models in text-to-optimization problems provides a clear roadmap for future AI development.
- · AI researchers focusing on structured reasoning
- · Specialized AI startups developing enterprise optimization solutions
- · Industries heavily reliant on complex optimization (logistics, finance, manufact
- · Generalist LLMs without specialized grounding architectures
- · Companies expecting out-of-the-box optimization from current LLMs
AI systems will require more sophisticated, hybrid architectures that combine large language models with symbolic reasoning or specialized grounding modules.
The development of highly accurate text-to-optimization systems could automate complex decision-making processes across various industries, leading to significant efficiency gains.
Improved AI capabilities in structured grounding might accelerate the development of truly autonomous AI agents capable of planning and executing complex tasks in the real world.
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Read at arXiv cs.LG