These improvements are not directly comparable because the four embeddings have different vocabularies (since they are trained on different datasets) and vocabulary sizes, their results cannot be directly compared.
we take an intersection of the vocabulary (i.e., the subset of words present in all four embeddings) and repeat all our experiments using these intersection files.