Revisiting Ripple Effects in Knowledge Editing through Pressure-Aware Joint Neighborhood Optimization

ArXi:2606.01610v1 Announce Type: new Single-edit updates in large language models can trigger ripple effects across local knowledge neighborhoods: desirable propagation to related facts and unintended perturbation of preserved ones. Existing methods address these two effects separately, without explicitly modeling their coupling. We challenge this separation through an analysis of ripple responses across typical baselines, identifying two coupled design pressures: editable-side coordination and preserved-side leakage.