Feb. 9, 2024, 5:43 a.m. | Santiago Miret N M Anoop Krishnan

cs.LG updates on arXiv.org arxiv.org

Large Language Models (LLMs) create exciting possibilities for powerful language processing tools to accelerate research in materials science. While LLMs have great potential to accelerate materials understanding and discovery, they currently fall short in being practical materials science tools. In this position paper, we show relevant failure cases of LLMs in materials science that reveal current limitations of LLMs related to comprehending and reasoning over complex, interconnected materials science knowledge. Given those shortcomings, we outline a framework for developing Materials …

cases cond-mat.mtrl-sci cs.ai cs.cl cs.lg discovery failure language language models language processing large language large language models llms materials materials science paper practical processing research science show tools understanding world

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