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EngiAI: A Multi-Agent Framework and Benchmark Suite for LLM-Driven Engineering Design

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Molinari, Gioele, Felten, Florian, Massoudi, Soheyl, Fuge, Mark
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Artificial Intelligence Machine Learning Multiagent Systems
Accesso online:	Acceder al recurso
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