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Apr, 2023
上下文学习的贝叶斯催化剂优化
Bayesian Optimization of Catalysts With In-context Learning
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Mayk Caldas Ramos, Shane S. Michtavy, Marc D. Porosoff, Andrew D. White
TL;DR
为了实现无特征或结构调整的上下文学习回归,我们展示了一个提示系统,结合了不确定性,使得大语言模型能够以自然语言处理的方法进行催化剂或分子优化的贝叶斯优化,从而消除了训练或模拟的需要。
Abstract
large language models
(LLMs) are able to do accurate classification with zero or only a few examples (
in-context learning
). We show a prompting system that enables
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