retrieval-augmented generation (RAG)

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

• Retrieval-Augmented Generationconcept0.847
  UCCT interprets RAG as an anchoring variant that raises effective cohesion ρd
• Hypothesis: Retrieval-augmented generation raises effective cohesion ρdhypothesis0.747
  UCCT's theoretical prediction about how RAG maps onto the anchoring score
• Reflection Enhancement via Activation Additionmethod0.730
  Adding steering vector in forward direction to push model activations toward stronger reflective behavior.
• Activation Reconstructor (AR)method0.714
  Component of NLA that maps natural language explanations back to activations; truncated to first l layers of target model.
• autoregressive persistenceconcept0.707
  Baseline persistence of any probe direction arising from the autoregressive nature of LLMs, not specific to emotion content
• Autoregressive Samplingmethod0.703
  The mechanism by which LLMs generate text: drawing a token from the next-token distribution and appending it to context repeatedly
• Activation Similarityconcept0.702
  Model-independent feature comparison based on correlating activation vectors across a fixed diverse dataset
• Feedbackconcept0.702
  The mechanism by which each step's effect is evaluated against the life of the whole, guiding the unfolding.