Posterior-GAN: Towards Informative and Coherent Response Generation with Posterior Generative Adversarial Network
Table 1: The automatic metrics evaluation results. Higher is better. “(F)”, “(B)” and “(A)” represent Posterior-GAN with a forward generative discriminator, a backward generative discriminator and both two discriminators, respectively.
['DailyDialog Models', 'DailyDialog Dist-1', 'DailyDialog Dist-2', 'DailyDialog Dist-3', 'DailyDialog BLEU', 'DailyDialog Greedy', 'DailyDialog Average', 'DailyDialog Extrema']
DP-GAN effectively improves the response diversity by utilizing the language model cross-entropy rewards while the performance on BLEU and embedding-based similarities do not witness similar improvements in our settings. Posterior-GAN achieves the best performance on all the automatic evaluation metrics on both corpora, indicating the superiority of the query-response-future turn triple training, enabled by the forward and backward generative discriminators, in comparison with the state-of-the-art generative approaches. And the improvements of our model are significant with p≤0.001 (T-test).