{
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  "path": "/t/continuation-drm-transformer-from-open-geometry-to-negotiated-geometry-in-ai-alignment/176106#post_5",
  "publishedAt": "2026-05-24T00:13:13.000Z",
  "site": "https://discuss.huggingface.co",
  "textContent": "Thanks, Jean. I agree that the right next step is a matched perturbation + recovery test.\n\nOne 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.\n\nSo 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.\n\nThat 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.",
  "title": "[Continuation] DRM Transformer: From Open Geometry to Negotiated Geometry in AI Alignment"
}