  Automatic generation of graphic designs has recently received considerable
attention. However, the state-of-the-art approaches are complex and rely on
proprietary datasets, which creates reproducibility barriers. In this paper, we
propose an open framework for automatic graphic design called OpenCOLE, where
we build a modified version of the pioneering COLE and train our model
exclusively on publicly available datasets. Based on GPT4V evaluations, our
model shows promising performance comparable to the original COLE. We release
the pipeline and training results to encourage open development.
