Learning requires not just error detection but signed directional evaluation

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

• Granted that learning requires signed information, but why must the sign be felt? Why can't directional error be represented as a computational quantity without phenomenal character?question0.865
  The central objection the paper must answer to establish identity over mere correlation
• If in-context learning involves signed evaluation in the service of behavioral modification, then the thesis applies not only to training but to every inference-time interactionclaim0.768
  Extension of the thesis to deployed LLM inference via in-context learning
• If the internal representations corresponding to signed evaluation could be identified and their sign inverted, learning dynamics and experiential reports should invert togetherhypothesis0.762
  Third falsifiable prediction: any dissociation between inverted learning and inverted valence report would disconfirm the identity
• What factors determine the generalisation of learned alignment maps beyond training data?question0.748
  Open question about the gap between Theorem 1's existence proof and practical learnability
• For signed goal-relative evaluation, the gap between function and phenomenology that the conceivability argument requires cannot be coherently openedclaim0.739
  The paper's response to the hard problem of consciousness
• Learned features reflect the functionality of the model and not just the data distribution, as evidenced by interpretable downstream effects not used in dictionary learningclaim0.736
  Authors argue features are model properties because logit effects and ablations are consistent with feature interpretations
• Accuracy does not vary linearly with latent reflection directions; instead it follows a more non-linear mapping that requires deeper theoretical treatment.claim0.736
  Theoretical limitation identified by the authors distinguishing reflection from stylistic tasks.
• The direction of information increase is relative to the observer or user of the computationclaim0.735
  Example: 3×5→15 is a natural computation, but 15→3×5 (prime factorization) is also useful, showing that the 'gain' depends on the choice of normal form.