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Constrained Training Manifolds

Stabilize large-model training by restricting weight updates to curated manifolds that align with desired behaviors and safety envelopes.

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Deployment benefits

  • Alignment maintenance: Constrained fine-tuning keeps aligned behaviors intact even after domain adaptation.
  • Resource efficiency: Low-rank manifolds reduce parameter counts, saving memory and inference cost.
  • Certifiable properties: Some manifolds enable formal guarantees (e.g., Lipschitz bounds) helpful for regulatory review.
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