Instead of discarding a fixed number of PCs, we softly filter word vectors using matrix conceptors (Jaeger 2014; 2017) , which characterize the linear space of those word vector features having high variances -the features most contaminated by word frequencies according to <cite>Mu and Viswanath (2018)</cite> .