4 The boost in quality is naturally most pronounced when the HH DIALOGUE training set is small (i.e., where the learning curve is steepest), yielding an increase of up to 9.4 accuracy points, a 31% improvement.
even when the entire PER-SONACHAT dataset of 131k examples is used-a much larger dataset than what is available for most dialogue tasks-adding deployment examples is still able to provide an additional 1.6 points of accuracy on what is otherwise a very flat region of  For each column, the model using all three data types (last row) is significantly better than all the others, and the best model using only one type of self-feeding (FEEDBACK examples or HB DIALOGUE examples) is better than the supervised baseline in the first row (p < 0.05).