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What is Quantum-Inspired Neural Networks for NLP about?

This paper presents two end-to-end quantum-inspired deep neural networks, ICWE-QNN and CICWE-QNN, for binary text classification, leveraging complex word embedding based on quantum theory. The models improve text classification performance by effectively capturing linguistic features and addressing the challenges of polysemy in natural language processing. Experimental results demonstrate that these models outperform traditional methods in accuracy and F1-score across multiple datasets.

Author

kareem.sqm

Language

EN