Gala: Global LLM Agents for Text-to-Model Translation

• URL: http://arxiv.org/abs/2509.08970v2
• Date: Thu, 02 Oct 2025 19:55:18 GMT
• Title: Gala: Global LLM Agents for Text-to-Model Translation
• Authors: Junyang Cai, Serdar Kadioglu, Bistra Dilkina,
• Abstract summary: We introduce Gala, a framework that addresses this challenge with a global agentic approach.<n>Multiple specialized large language model (LLM) agents decompose the modeling task by global constraint type.<n>By dividing the problem into smaller, well-defined sub-tasks, each LLM handles a simpler reasoning challenge.
• Score: 12.20235137210144
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Natural language descriptions of optimization or satisfaction problems are challenging to translate into correct MiniZinc models, as this process demands both logical reasoning and constraint programming expertise. We introduce Gala, a framework that addresses this challenge with a global agentic approach: multiple specialized large language model (LLM) agents decompose the modeling task by global constraint type. Each agent is dedicated to detecting and generating code for a specific class of global constraint, while a final assembler agent integrates these constraint snippets into a complete MiniZinc model. By dividing the problem into smaller, well-defined sub-tasks, each LLM handles a simpler reasoning challenge, potentially reducing overall complexity. We conduct initial experiments with several LLMs and show better performance against baselines such as one-shot prompting and chain-of-thought prompting. Finally, we outline a comprehensive roadmap for future work, highlighting potential enhancements and directions for improvement.

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