In scenarios with recurring distribution shifts, Xenovert demonstrates robust performance compared to other adaptive algorithms. Xenovert's ability to dynamically adjust quasi-quantiles based on the input stream allows it to continuously adapt to changing distributions over time. This adaptability enables Xenovert to effectively handle recurring shifts without the need for frequent retraining, saving computational resources and time. Additionally, Xenovert's uniform division of the input space and preservation of data relationships contribute to its stable performance in scenarios with recurring distribution shifts, outperforming other adaptive algorithms that may struggle to maintain accuracy in such dynamic environments.