We trained 100-dimensional skip-gram vectors (Mikolov et al., 2013) on English Wikipedia (tokenized/lowercased, resulting in 1.8B tokens of text) using window size 10, hierarchical softmax, and no downsampling.
if the current word is a local context word, we sample a new topic/sense pair for it again conditioned on all other latent variable values.