Quantum Natural Language Processing: Challenges and Opportunities

The meeting between Natural Language Processing (NLP) and Quantum Computing has been very successful in recent years, leading to the development of several approaches so-called (QNLP). This is a hybrid field which potential quantum mechanics exploited applied critical aspects language processing, involving different NLP tasks. Approaches developed so far span from those that demonstrate advantage only at theoretical level ones implementing algorithms on hardware. paper aims list far, categorizing them by type, i.e., work implemented classical or hardware; task, general purpose such as syntax-semantic representation specific tasks, like sentiment analysis question answering; resource used evaluation phase, whether benchmark dataset custom one used. advantages offered QNLP are discussed, both terms performance methodology, some considerations about possible usage place state-of-the-art deep learning-based given.