Progress in science depends on new techniques, new discoveries and new ideas, probably in that order. - Sydney Brenner
we believe that building the right tools is essential for making progress in science.
a focus of our work has been on developing benchmarks (“benches”) to understand the capabilities and limitations of machine learning models in chemistry and materials science.
benches
ChemBench
testing the chemical capabilities of llms
learn more >MaCBench
probing vision-language models in materials science and chemistry.
learn more >MatText
testing the limits of (l)lms in modeling materials
learn more >data
ChemPile
large-scale dataset for chemical language models
learn more >books
MatExtract
data extraction online tutorial for materials science
learn more >GPMs book
online book on general-purpose models in chemistry and materials science
learn more >
