ELMo creates contextualized representations of each token by concatenating the internal states of a 2-layer biLSTM trained on a bidirectional language modelling task (Peters et al., 2018).
recall from Definition 3 that the maximum explainable variance (MEV) of a word, for a given layer of a given model, is the proportion of variance in its contextualized representations that can be explained by their first principal component.