Pretraining exposure density

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

• Shot midpoint ordering k50(B10) < k50(B8) ≈ k50(B9) tracks pretraining exposure densityclaim0.760
  Interpretation that pattern density from pretraining determines few-shot requirements
• Pre-Encoder Biasconcept0.735
  Architectural modification subtracting a learned bias from autoencoder inputs before encoding; initialized to geometric median of dataset; improves autoencoder performance
• Hypothesis: Shot midpoint ordering k50(B10) < k50(B8) ≈ k50(B9) follows pretraining exposure densityhypothesis0.719
  E2 prediction that bases with higher pretraining exposure require fewer shots to cross threshold
• Recognition Densityconcept0.715
  Approximate posterior probability distribution embodied in organism's internal states; organism's best guess about causes of sensations
• Pretraining stores latent patterns that coherent anchors can bind (or misbind) to targets.quote0.709
  Load-bearing quote capturing the core metaphor
• Post-training is key to eliciting strong introspective awareness; base pretrained models do not show above-chance detectionclaim0.696
  Finding that base models have high false positives and no net positive performance.
• Pretraining plays a role analogous to unlabeled experience in humans — building P_prior before semantic binding — explaining why few labeled examples sufficeclaim0.693
  Developmental analogy used to explain sample efficiency under high ρd conditions
• Exploratory activity level (temperature)concept0.693
  The plasticity or willingness of cells to move; raised by stress sharing, analogous to annealing temperature.