We see from this figure that the performance of both fZM and GIGP improves dramatically when they are trained and tested on randomized sequences of words.
we can ignore the issue of what is the boundary between topical words to be echo-adjusted and general words, as long as we can be confident that the set of lowest frequency words used for model fitting belong to the topical set.