Hongbo Guo

More Data, Worse Decisions? Preference Reversals in Neural Networks under Gram Incompatibility

This work shows that pooled refitting recomputes the inverse-Gram geometry used to weight source evidence, which can reverse shared preferences, and derive exact and approximate preservation conditions, and develops a three-stage audit that traces strict pairwise reversals through decision changes to task-defined utility loss.