APA (7th ed.) Citation

Zhu, J., Fan, Y., Han, G., Shi, X., Deng, F., & Chen, J. (2026). Generative anomaly detection: A comprehensive review of modeling principles, advances, and future opportunities. Artificial Intelligence Review, 59(9), 1. https://doi.org/10.1007/s10462-026-11591-w

Chicago Style (17th ed.) Citation

Zhu, Jiaqi, Yunfeng Fan, Geng Han, Xiang Shi, Fang Deng, and Jie Chen. "Generative Anomaly Detection: A Comprehensive Review of Modeling Principles, Advances, and Future Opportunities." Artificial Intelligence Review 59, no. 9 (2026): 1. https://doi.org/10.1007/s10462-026-11591-w.

MLA (9th ed.) Citation

Zhu, Jiaqi, et al. "Generative Anomaly Detection: A Comprehensive Review of Modeling Principles, Advances, and Future Opportunities." Artificial Intelligence Review, vol. 59, no. 9, 2026, p. 1, https://doi.org/10.1007/s10462-026-11591-w.