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@article{174641,
        author = {Aditee Bhosale and Prajkta Patil and Siddhi Kolekar and Aatharv Durugade and Neha Bamane and suyash Bange and Kaustubh Joshi and Abhijeet Paritekar},
        title = {A Review Paper On Quantum Generative AI},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {683-688},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174641},
        abstract = {Quantum Generative AI (QGAI) combines quantum computing with artificial intelligence to enhance capabilities in data generation, optimization, and pattern detection. By utilizing quantum mechanics principles such as superposition and entanglement, it significantly improves speed, efficiency, and computational power in comparison to traditional generative models. QGAI contributes to advancements in drug development, cryptography, material science, and creative applications of AI. However, the implementation of quantum AI presents challenges, including hardware limitations, noise in quantum systems, and complex algorithms. This paper explores the advancements, uses, and potential of QGAI and its capacity to transform artificial intelligence and computing.},
        keywords = {Quantum Generative AI, Quantum Computing, Artificial Intelligence, Quantum Neural Networks, Quantum Machine Learning, Quantum GANs, Quantum Optimization, Quantum Algorithms.},
        month = {March},
        }