Before revision:  In this work, we utilize mean-field theoretic manifold analysis, a recent technique from computational neuroscience  , to analyze the high dimensional geometry of language representations from large-scale contextual embedding models.
After revision:  In this work, we utilize mean-field theoretic manifold analysis, a recent technique from computational neuroscience that connects geometry of feature representations with linear separability of classes , to analyze the high dimensional geometry of language representations from large-scale contextual embedding models.