Embeddings to summarize documents

I'm looking for different ways to summarize documents with vector embeddings

* centroid of word2vec embeddings
* doc2vec but in terms of distributed bag of words since word order doesn't really matter for this particular task
* The CLS embedding of Bert

To be economic, I plan to keep only the top 20 tf-idf words of each document. For that reason, word order is completely arbitrary.

bag bag of words bert datascience distributed documents economic embedding embeddings terms tf-idf vector vector embeddings word word2vec words