Recurrent Quantum Embedding Neural Network And Its Application In Vulnerability Detection

This article discusses the potential benefits of combining quantum computing with natural language processing (NLP) in order to reduce computing costs. The DisCoCat model is commonly used as a theoretical framework for QNLP methods, but has only been tested on small datasets and not yet applied to real-world tasks. Other methods, such as RQNN and QLSTM, have also been proposed but are still far from practical application. The article highlights the challenges and potential for further development in this field.