The fact that gLDA+SVM performs better than the standard gSLDA is due to the same reason, since the SVM part of gL-DA+SVM can well capture the supervision information to learn a classifier for good prediction, while standard sLDA can't well-balance the influence of supervision.
the well-balanced gSLDA+ model successfully outperforms the twostage approach, gLDA+SVM, by performing topic discovery and prediction jointly 4 .