In this section, we describe the word embedding results, where we directly compare our model with the following baselines: GloVe (Pennington et al., 2014), Skipgram (Mikolov et al., 2013b) (denoted as SG), Continuous Bag of Words (Mikolov et al., 2013b) (denoted as CBOW), and the recently proposed WeMAP model (Jameel et al., 2019).
our method is clearly different from these works, as our focus is on learning standard word vectors (as well as document vectors).