The asymmetric features take inspiration from Mikolov, Yih, and Zweig (2013), who found that differences between distributional vectors often encode certain linguistic regularities, like king − man + woman ≈ queen.
the asymmetric classifier uses two sets of features, < f, g >, where: that is, the vector difference between the LHS and the RHS, and this difference vector squared.