We sincerely thank the reviewer for the constructive feedback. To address the concerns regarding figure clarity and overlapping curves, we have redesigned the visualizations into
These figures demonstrate the universality and robustness of the Privacy Manifold across all 5 evaluated LLM families.
Redesigned Figure 2 from the original submission. As shown below, the Semantic Sweet Spot (40%-70% depth) are consistent, standalone phenomena across every single model family.
Redesigned Figure 4(d) from the original submission. The curves show that the probe achieves extreme sample efficiency, converging to near-optimal performance (>99% AUROC) with as few as 64 training samples across all architectures.
