The scientific corpus contains both common words (e.g., "propose", "experiment") and domain-specific words, such as "submodular" and "sublinear".
our method takes less than one minute to insert about 1,000 domain-specific words (e.g., machine learning related words from NIPS abstracts) into a pre-trained embedding model with more than 180,000 words.