Frobenius Norm Composition Measurement

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

• Frege Compositionalityconcept0.720
  Formal linguistic principle: meaning of a whole depends only on meanings of parts and how they are fitted together (bottom-up meaning flow).
• In the analyzed two-layer attention-only model, only K-composition is significant; V- and Q-composition are negligible by Frobenius norm measurefinding0.714
  Result from applying the Frobenius norm composition measurement to all attention head pairs in the two-layer model
• Maximum gradient norm scalingconcept0.702
  Scaling aggregated gradient by the maximum gradient norm among tasks.
• maximum-norm gradient normalizationmethod0.678
  Training-free technique normalizing all task gradients to the maximum gradient norm magnitude
• Schrödinger Compositional Theoryconcept0.678
  Process theory variant where composition is non-trivial (whole cannot be decomposed meaningfully) and all ingredients have clear ontological counterparts in reality.
• Compositionalityconcept0.674
  Central concept: how meaning of wholes depends on meanings of parts and their structural arrangement; multiple formulations explored (Frege, Schrödinger, Whitehead, LEGO).
• Fine-Tuning Threshold Recalibrationmethod0.672
  Re-running probabilistic bisection on each fine-tuned checkpoint to normalize first-attempt difficulty
• Self-Correction Data Mixing Ratioconcept0.669
  Experimental variable sweeping proportion of self-correction to normal response training examples from 10% to 90%