Proceedings of the National Academy of Sciences, Volume 123, Issue 18, May 2026. SignificanceThis work introduces a model-agnostic framework for training and inference to enable accurate partial differential equation solving (down to double precision) for problems with arbitrary sizes and parameters, bridging the gap between problem-β¦