Discovering Ordinary Differential Equations with LLM-Based Qualitative and Quantitative Evaluation

arXiv cs.AI · 18 hours ago

Researchers developed DoLQ, a method that uses large language models to discover ordinary differential equations from observational data by combining qualitative and quantitative evaluation through a multi-agent architecture. The system achieved higher success rates than existing methods on multi-dimensional ordinary differential equation benchmarks. By incorporating domain knowledge assessment through LLMs alongside traditional quantitative metrics, the approach improves accuracy in recovering correct symbolic terms of equations.