April 3, 2024, 4:41 a.m. | Adrian Mirza, Nawaf Alampara, Sreekanth Kunchapu, Benedict Emoekabu, Aswanth Krishnan, Mara Wilhelmi, Macjonathan Okereke, Juliane Eberhardt, Amir Moh

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.01475v1 Announce Type: new
Abstract: Large language models (LLMs) have gained widespread interest due to their ability to process human language and perform tasks on which they have not been explicitly trained. This is relevant for the chemical sciences, which face the problem of small and diverse datasets that are frequently in the form of text. LLMs have shown promise in addressing these issues and are increasingly being harnessed to predict chemical properties, optimize reactions, and even design and conduct …

abstract arxiv cond-mat.mtrl-sci cs.ai cs.lg datasets diverse face form human language language models large language large language models llms physics.chem-ph process small superhuman tasks type

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