[Continuation] DRM Transformer: From Open Geometry to Negotiated Geometry in AI Alignment

Thanks, Jean. I agree that the right next step is a matched perturbation + recovery test. One clarification: DRM has already reached a T²-like toroidal closure regime at ~3.5M parameters. It is not yet strict stable closure under the current criterion, since stable remains <= 0.60, but the toroidal signature is already there. So the contribution is not that DRM has fully stabilized closed geometry yet. The contribution is that a very small model, trained from the beginning inside a geodesic/relational manifold, can already enter an unstable or near-stable T²-like regime. That is exactly why I think the architecture matters. Standard Transformers may exhibit measurable emergent geometry, but DRM is testing whether topology can be induced directly and then stabilized.