Taking the argument classes produced by the linguistic model as a basis and then re-ranking them to incorporate visual statistics helps to avoid the above problem for the interpolated models, whose output corresponds to grammatical relations.
static interpolation weights (emphasizing linguistic features over the visual ones for all verbs equally) outperformed the predicate-driven interpolation technique, attaining correlations of r = 0.548 and r = 0.476 respectively.