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Article summary:
1. Investigating response generation for multi-turn dialogue in generative-based chatbots.
2. Introducing a Pseudo-Variational Gated Recurrent Unit (PVGRU) component to capture subtle semantic variability.
3. Building a Pseudo-Variational Hierarchical Dialogue (PVHD) model based on PVGRU, which improves the diversity and relevance of responses on two benchmark datasets.
Article analysis:
The article is generally trustworthy and reliable, as it provides evidence for its claims through experimental results demonstrating that PVGRU can broadly improve the diversity and relevance of responses on two benchmark datasets. The article does not appear to be biased or one-sided, as it presents both sides of the argument equally and does not make any unsupported claims. Furthermore, there are no missing points of consideration or missing evidence for the claims made, as all relevant information is provided in the article. Additionally, there is no promotional content or partiality present in the article, as it objectively presents both sides of the argument without favoring either side. Finally, possible risks are noted throughout the article, making it clear that further research needs to be done before any conclusions can be drawn from this study.