[zacmps]

It depends. Usually a paper doesn't have enough room to mention all of the possible choices in preprocessing, architecture, optimiser, etc. You can usually get pretty close with details just in the paper, but it's not always possible.

That's why a large number of journals now have requirements for publishing code and/or pretrained models (if applicable).

An annoying trend I've noticed in a number of SotA ML papers in video classification present multiple models and only publish the exact architecture & weights for the smaller models which are only as-good-as SotA (see tiny video networks, X3D for examples).