Quantum neural networks have been widely studied in recent years, given their potential practical utility and results regarding ability to efficiently express certain classical data. However, analytic date rely on assumptions arguments from complexity theory. Due this, there is little intuition as the source of expressive power quantum or for which classes data any advantage can be reasonably e...

Contrastive learning models have achieved great success in unsupervised visual representation learning, which maximize the similarities between feature representations of different views same image, while minimize images. In text summarization, output summary is a shorter form input document and they similar meanings. this paper, we propose contrastive model for supervised abstractive where vie...