Multi-Granularity Representations of Dialog
Table 4: Results of the granularity analysis experiment. L=5 models trained to capture different granularities of representation. All bold-face results are statistically significant to p<0.01.
['[BOLD] Model Name', '[BOLD] BoW (F-1)', '[BOLD] DA (F-1)']
It is clear that higher granularity models better capture the information necessary for the bag-of-words task, while higher abstraction (lower granularity) models better capture information for dialog act prediction.