The Dawn of Quantum Natural Language Processing

10/13/2021

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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.

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The Dawn of Quantum Natural Language Processing

Applying QNLP to sentiment analysis in finance

Parts of Speech Tagging in NLP: Runtime Optimization with Quantum Formulation and ZX Calculus

Quantum Optical Experiments Modeled by Long Short-Term Memory

Quantum deep recurrent reinforcement learning

Automatic Rule Extraction from Long Short Term Memory Networks

Q-LSTM Language Model – Decentralized Quantum Multilingual Pre-Trained Language Model for Privacy Protection

Adiabatic Quantum Computing for Binary Clustering

The Dawn of Quantum Natural Language Processing

Related Research

Applying QNLP to sentiment analysis in finance

Parts of Speech Tagging in NLP: Runtime Optimization with Quantum Formulation and ZX Calculus

Quantum Optical Experiments Modeled by Long Short-Term Memory

Quantum deep recurrent reinforcement learning

Automatic Rule Extraction from Long Short Term Memory Networks

Q-LSTM Language Model – Decentralized Quantum Multilingual Pre-Trained Language Model for Privacy Protection

Adiabatic Quantum Computing for Binary Clustering