Self-correcting search with interpretability feedback

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Self-Correcting Searchmethod0.875
  Technique using internal model representations as feedback loops to steer diffusion-based materials generation toward target properties.
• interpretabilityconcept0.784
  The capability to explain model predictions; a central theme of the paper, with disruption profiles as vehicle.
• Self-Correctionconcept0.782
  Reasoning pattern where model reverses a compliance tendency and returns toward refusal, associated with better safety in QwQ-32B
• Self-correcting search applicable to protein design / drug discoveryclaim0.778
  Claim by the authors that the self-correcting search method can be extended to protein design and drug discovery.
• Interpretability-Driven Feedback Steeringconcept0.772
  Framework of using internal-state representations to control or steer generative models; conceptually parallel to manifold steering in language models.
• Self-correcting search is Pareto-optimal across tested conditioning strengths.claim0.765
  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 LMsclaim0.762
  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.finding0.757
  Main empirical result: interpretability-driven feedback increases discovery efficiency significantly.