AI RESEARCH
Material Database Agent: A Multimodal Agentic Framework for Scientific Literature Mining
arXiv CS.CL
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ArXi:2605.04278v1 Announce Type: new Materials science workflows rely on structured and unstructured data from the vast body of available scientific literature. However, most of the experimental details remain buried in text, tables, graphs and figures. Thus, constructing databases that incorporate this data is a manual, time-consuming, and hard-to-scale process. Multimodal large language models have made it feasible to extract information from text and scientific figures with high speed and accuracy.