This document summarizes the lda2vec model, which combines aspects of word2vec and LDA. Word2vec learns word embeddings based on local context, while LDA learns document-level topic mixtures. Lda2vec models words based on both their local context and global document topic mixtures to leverage both approaches. It represents documents as mixtures over sparse topic vectors similar to LDA to maintain