@inproceedings{phukan-ekbal-2025-survey,
    title = "A Survey of Quantum Natural Language Processing: From Compositional Models to {NISQ}-Era Empiricism",
    author = "Phukan, Arpan  and
      Ekbal, Asif",
    editor = "Pal, Santanu  and
      Pakray, Partha  and
      Jain, Priyanka  and
      Ekbal, Asif  and
      Bandyopadhyay, Sivaji",
    booktitle = "Proceedings of the QuantumNLP{\{}:{\}} Integrating Quantum Computing with Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Mumbai, India (Hybrid)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.quantumnlp-1.9/",
    pages = "65--75",
    ISBN = "979-8-89176-306-7",
    abstract = "Quantum Natural Language Processing (QNLP) has emerged as a novel paradigm that leverages the principles of quantum mechanics to address fundamental challenges in language modeling, particularly in capturing compositional meaning. This survey charts the evolution of QNLP, from its theoretical foundations in the Distributional Compositional Categorical (DisCoCat) framework to its modern implementation on Noisy Intermediate-Scale Quantum (NISQ) hardware. We review the primary architectural approaches, including variational quantum circuits and tensor networks, and summarize the growing body of empirical work in tasks such as text classification, sentence similarity, and question answering. A recurring finding is the potential for QNLP models to achieve competitive performance with significantly fewer parameters than their classical counterparts. However, the field is critically constrained by the limitations of NISQ-era hardware. We conclude by discussing these challenges and outlining the future trajectory towards achieving a demonstrable quantum advantage and building more interpretable, efficient language models."
}