The Dawn of Quantum Natural Language Processing
This work addresses the challenge of improving NLP performance for researchers and practitioners by integrating quantum computing, but it appears incremental as it builds on existing deep-learning models with quantum enhancements.
The paper tackles the problem of enhancing natural language processing tasks using quantum computing, achieving successful training of a quantum-enhanced LSTM for parts-of-speech tagging and proposing a quantum-enhanced Transformer for sentiment analysis.
In this paper, we discuss the initial attempts at boosting understanding human language based on deep-learning models with quantum computing. We successfully train a quantum-enhanced Long Short-Term Memory network to perform the parts-of-speech tagging task via numerical simulations. Moreover, a quantum-enhanced Transformer is proposed to perform the sentiment analysis based on the existing dataset.