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Responsible AI in Construction Safety: Systematic Evaluation of Large Language Models and Prompt Engineering

dc.contributor.authorSammour, Farouq
dc.contributor.authorXu, Jia
dc.contributor.authorWang, Xi
dc.contributor.authorHu, Mo
dc.contributor.authorZhang, Zhenyu
dc.date.accessioned2026-08-20T21:36:30Z
dc.date.available2026-08-20T21:36:30Z
dc.date.copyright2025/10/24
dc.date.issued2026
dc.identifier.otherJCEMD4.COENG-16639.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314728
dc.description.abstractAbstractResponsible artificial intelligence (AI) in construction safety requires rigorous, domain-specific evaluation. Deploying large language models (LLMs) without understanding their capabilities and limitations risks generating inaccurate information ...
dc.publisherAmerican Society of Civil Engineers
dc.titleResponsible AI in Construction Safety: Systematic Evaluation of Large Language Models and Prompt Engineering
dc.typeJournal Article
dc.journal.volume152
dc.journal.issue1
dc.journal.titleJournal of Construction Engineering and Management
dc.identifier.doi10.1061/JCEMD4.COENG-16639
dc.journal.fristpage04025217-1
dc.journal.lastpage04025217-15
dc.page15
dc.treeJournal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 001
dc.contenttypeFulltext


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