Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System
Automatic scientific discovery has long been a goal of computational scholars - a machine that can discover nature's secrets on its own, moving computational systems beyond data-fitting tools toward the generation and refinement of mechanistic models of the universe. Recent advances in symbolic regression (SR) and large-language-model (LLM)-based agents suggest that such systems can recover equations from data, incorporate domain priors, and automate parts of the research workflow. However, most
Record details
Published: 15 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Agents & autonomy · Biotech
Retrieved: 16 July 2026
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ethics.ai (15 July 2026), “Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System,” evidence record 10917, https://ethics.ai/record/10917 (originally published by arXiv cs.AI).
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