In the remainder of this paper, 'wx' = means word embeddings of size x for a word-level model and 'cx' means character embeddings of size x for CW models.
they only compare to a simple baseline model of 2 LSTM layers of each 200 hidden units without dropout, resulting in a higher baseline perplexity (as mentioned in section 4.3, our CW model also achieves larger improvements than reported in this paper with respect to that baseline).