BIBREF25 also proposed the idea of using average of word embeddings to represent the global context of a document. Different from their work, we choose to corrupt the original document by randomly removing significant portion of words, and represent the document using only the embeddings of the words remained. 
 Question: Is their approach similar to making an averaged weighted sum of word vectors, where weights reflect word frequencies?
Different from their work, we choose to corrupt the original document by randomly removing significant portion of words, and represent the document using only the embeddings of the words remained.