5 Moreover, since these methods use asymptotic Gaussian or Cauchy random projection matrices R with E(R) = 0, their resulting vectors cannot be adjusted and transformed using weighting techniques such as PPMI.
these methods often do not outperform neural embeddings and combinations of PPMI weighting of count-based models followed by matrix factorization-such as the truncation of weighted vectors using singular value decomposition (SVD).