Yi Zhou, Parikshit Ram, et al.
ICLR 2023
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.
Yi Zhou, Parikshit Ram, et al.
ICLR 2023
Sashi Novitasari, Takashi Fukuda, et al.
INTERSPEECH 2025
Tim Erdmann, Stefan Zecevic, et al.
ACS Spring 2024
Shachar Don-Yehiya, Leshem Choshen, et al.
ACL 2025