Potential counterarguments against utilizing filtered structural information in guiding clustering processes may include concerns about overfitting or bias introduced by relying too heavily on past data. Critics may argue that storing and using historical correlations could lead to models becoming less adaptable to changes in newer data patterns or distributions. There might also be challenges related to privacy and security if sensitive or outdated information is retained within the filtered structure buffer. Additionally, some researchers may question the scalability of this approach when dealing with large datasets or high-dimensional feature spaces.