If i is 1, the word w is generated according to topic-word distribution P (w|z ds , C w , M ), which is defined as follows: In Eq.
(1), C w stands for the sliding window for w. C w contains several words that precedes w. where M = {v w , v z } stands for the word embedding and the topic embedding, x w is the result of element-wise addition of the word embeddings of C w and the topic embedding indexed by z ds (i.e.,  In Section 4.1, we describe how to sample the latent topics for sentences.