First, we have demonstrated that a model using all these features to predict content patterns in subsequent references in shared visual scenes delivers an Accuracy of 58.8% and a DICE score of 0.81, outperforming models based only on features inspired by one of the two approaches.
we found that the features based on traditional REG considerations do not contribute as much to this score as those based on the alignment approach, and that dropping the traditional REG features does not significantly hurt the performance of a model based on alignment and theory-independent features.