Kellen Cheng, Anna Lisa Gentile, et al.
EMNLP 2024
Large language models, commonly known as LLMs, are showing promise in tacking some of the most complex tasks in AI. In this perspective, we review the wider field of foundation models—of which LLMs are a component—and their application to the field of materials discovery. In addition to the current state of the art—including applications to property prediction, synthesis planning and molecular generation—we also take a look to the future, and posit how new methods of data capture, and indeed modalities of data, will influence the direction of this emerging field.
Kellen Cheng, Anna Lisa Gentile, et al.
EMNLP 2024
Baihan Lin, Guillermo Cecchi, et al.
IJCAI 2023
Zhikun Yuen, Paula Branco, et al.
DSAA 2023
Susan L. Spraragen
International Conference on Design and Emotion 2010