Large language models as uncertainty-calibrated optimizers for experimental discovery
Summary
Nature Machine Intelligence, Published online: 28 August 2026; doi:10.1038/s42256-026-01283-z Although language models can be helpful in molecular design, they are not typically calibrated for uncertainty. Rankovic and colleagues present a method to train language models while taking into account the uncertainty of the data.
Evidence & checks
- Discovery channel
- Nature Portfolio · Nature Machine Intelligence
- Original material
- www.nature.com
- Material type
- Source page; material type not verified
- Material basis
- Retrieval basis unknown
- Review status
- No human-review record