Table lists a non-exhaustive selection of studies based on Chemprop, showcasing its versatility and applicability for the prediction of a large variety of chemical properties, but also its ease of use. Models can be trained and tested with a single line on the command line (or a few lines of python code) and a user-supplied CSV file (See SI for some examples). In the following, we discuss specialty options introduced since its first release.