AI RESEARCH
Discovering Ordinary Differential Equations with LLM-Based Qualitative and Quantitative Evaluation
arXiv CS.AI
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ArXi:2605.07323v1 Announce Type: new Discovering governing differential equations from observational data is a fundamental challenge in scientific machine learning. Existing symbolic regression approaches rely primarily on quantitative metrics; however, real-world differential equation modeling also requires incorporating domain knowledge to ensure physical plausibility. To address this gap, we propose DoLQ, a method for discovering ordinary differential equations with LLM-based qualitative and quantitative evaluation.