Self-correcting search applicable to protein design / drug discovery

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• Self-Correcting Searchmethod0.838
  Technique using internal model representations as feedback loops to steer diffusion-based materials generation toward target properties.
• Self-correcting search with interpretability feedbackconcept0.778
• Self-correcting search is Pareto-optimal across tested conditioning strengths.claim0.775
  Asserts that the method maintains efficiency across a range of constraint strengths without degradation.
• Self-correcting search employs the same conceptual move as Wurgaft's manifold steering, applied to chemistry instead of LMsclaim0.770
  Interpretive assertion that the internal-state feedback mechanism mirrors manifold steering from prior work.
• Self-correcting search yields ~+30% improvement in viable candidates within target bandgap range.finding0.747
  Main empirical result: interpretability-driven feedback increases discovery efficiency significantly.
• Synthetic Self-Correction Fine-Tuningmethod0.739
  Fine-tuning on Claude-generated self-correction examples with loss masking to induce ESR-like behavior
• Protein designconcept0.732
  Application domain suggested for the method, involving generation of protein structures.
• Internal-state feedback steering is applicable to protein design and drug discovery beyond materials.claim0.732
  Generalizes the mechanism to other molecular design domains.