Hypothesis: Retrieval-augmented generation raises effective cohesion ρd

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

• An AI persona achieves coherence by echoing itself consistently without templating—requiring claim about memory and voice fidelity.claim0.761
• Can natural language explanations of activations generated through unsupervised reconstruction genuinely capture model cognition?question0.754
  Core research question motivating NLA development and validation through case studies and causal interventions.
• Fine-tuning reduces mismatch dr, retrieval increases effective cohesion ρd, and few-shot adjusts the budget kclaim0.750
  Unified interpretation of different adaptation methods via UCCT terms
• Ali et al. 2025 found contrastive activation addition less effective at larger model scale, consistent with ESR in 70Bfinding0.749
  Prior finding from related work that aligns with ESR being strongest in the largest model tested
• Artifacts can stabilize and make intersubjectively sharable aesthetic experiences of action.claim0.749
  Core thesis: refutes Saito's concern by showing designed artifacts structure process aesthetics similarly to object arts.
• Building AI systems with more indicator properties will increase the likelihood of consciousness.hypothesis0.747
  Guiding hypothesis of the rubric.
• Stress sharing works to increase cohesiveness of collectives by raising exploratory plasticity in neighboring cells, enabling long-distance cell influencehypothesis0.747
• retrieval-augmented generation (RAG)method0.747
  Retrieving external content to augment prompts.