A Formal Analysis of Multimodal Referring Strategies Under Common Ground
Table 1: Classification accuracy after 1000 epochs using formal features (mean and standard deviation over 7-fold cross-validated sample)
['[EMPTY]', '[BOLD] Raw features', '[BOLD] Raw feat. + SE']
The raw features extracted from the EMRE dataset are successful in predicting the correct quintile of annotator judgment of the associated multimodal referring strategy approximately \sfrac23 of the time. Interestingly, the addition of sentence embeddings caused the average accuracy to drop about 3.28%, suggesting that sentence embeddings caused some confusion in the classifier.