Knowledge-Grounded Agentic Large Language Models for Multi-Hazard Understanding from Reconnaissance Reports
机构 * organization= Department One , addressline= Address One , city= City One , postcode= 00000 , state= State One , country= Country One ； organization= Department Two , addressline= Address Two , city= City Two , postcode= 22222 , state= State Two , country= Country Two ； organization= Zachry Department of Civil \& Environmental Engineering, Texas A\&M University , addressline= 3136 TAMU , city= College Station , postcode= 77843 , state= TX , country= USA ； organization= Department of Engineering Technology ； Industrial Distribution, Texas A\&M University , city= College Station , postcode= 77843 , state= TX , country= USA ； organization= Department of Civil ； Environmental Engineering, University of Illinois Urbana-Champaign , city= Urbana , postcode= 61801 , state= IL , country= USA
Comments 17 pages, 5 figures
