arXiv:2604.19789v1 Announce Type: new Abstract: We present an autonomous large language model (LLM) agent for end-to-end, data-driven materials theory development. The model can choose an equation form, generate and run its own code, and test how well the theory matches the data without human intervention. The framework combines step-by-step reasoning with expert-supplied tools, allowing the agent
From Data to Theory: Autonomous Large Language Model Agents for Materials Science
Samuel Onimpa Alfred, Veera Sundararaghavan·arXiv cs.AI··1 min read
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