Differences in persona vector geometry across checkpoints correspond to meaningfully different versions of the persona

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

• Sharp persona vector transitions occur at different layers than general hidden vector transitions, demonstrating persona-specific rather than generic computational boundariesfinding0.824
  Rules out the confound that persona transitions merely reflect universal computational phase changes
• Cosine Similarity of Persona Vectorsconcept0.813
  Geometric measure used to track persona vector drift and stability across checkpoints
• Cosine similarity between earliest extractable checkpoint persona vector and final-pretraining direction starts at approximately 0.3finding0.809
  Quantifies geometric distance of early persona directions from final direction
• There may exist a natural 'persona basis' characterizing the space of all model personas, with correlations between persona vectors predicting co-expression of traitshypothesis0.806
  Open question proposed by authors for future work on the dimensionality and structure of persona space
• Persona Vector Extraction via Difference-of-Meansmethod0.806
  Core method for extracting persona vectors by contrasting mean activations under persona-eliciting vs. suppressing prompts
• Persona Vector Arithmeticconcept0.806
  Compositional combination of persona vectors via algebraic operations on activation directions
• What dimensions of persona are not captured by our extracted role vectors, and how complete is the current persona space mapping?question0.803
  Limitation question motivating future work on persona elicitation strategies
• Persona vectors do not emerge as a single capability; each persona has its own onset and ceiling ordered by prevalence and behavioral simplicity in pretraining dataclaim0.801
  Interpretive finding against a unified emergence threshold for all personas