We would also like to point out that, as can be seen in the table, our results have quite high variance -the main source of it is the nature of our training/evaluation setup where we average over 10 runs with 10 different sets of seed dialogues.
in the majority of cases with comparable means, DiKTNet has a lower variance than    The comparison of the setups with different latent representations also gives us some insight: while the VAE-powered HRED model improves on the baseline in multiple cases, it lacks generalization potential compared to the LAED setup.