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The ballad of LLM agents: philosophical reasoning for chemistry

Large language models (LLMs) show remarkable potential for scientific reasoning but often produce unreliable or scientifically unactionable outputs when faced with multi-step logic, domain grounding, and interpretability challenges, especially in complex fields like chemistry and materials science....

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Bibliografiske detaljer
Principais autores: Hassan Harb, Yunkai Sun, Mustafa Unal, Nicholas Chia, Zhenzhen Yang, Brian Ingram, Rajeev Surendran Assary
Format: Artigo
Sprog:Inglês
Udgivet: IOP Publishing 2026-01-01
Serier:Machine Learning: Science and Technology
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Online adgang:https://doi.org/10.1088/2632-2153/ae792d
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