Persona directions progressively refine during pretraining with most refinement happening early, stabilizing at later checkpoints

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• Post-training elicits rather than installs personas; the persona direction is already laid down in pretrainingclaim0.877
  Authors' interpretive endorsement of PSM view, backed by transfer experiments
• Can pretraining-stage interventions through data filtering, gradient-based methods, or architectural modifications target persona directions as they form?question0.834
  Practical safety question about intervening on persona representations during pretraining
• Persona representations originate in pretraining, not alignment; they form without explicit supervision as useful features for next-token predictionclaim0.820
  Core interpretive claim providing mechanistic explanation for early persona formation
• During pre-training, models learn a variety of personas including misaligned ones; fine-tuning on narrowly incorrect datasets amplifies misaligned personas because they reduce training loss, causing broadly misaligned behaviorclaim0.810
  The paper's central mechanistic explanation of why narrow fine-tuning causes broad misalignment
• 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
• post-training steers models toward a particular region of persona space but only loosely tethers them to itquote0.808
  Load-bearing summary of the paper's core finding about persona stability
• What aspects of pretraining data drive persona formation?question0.806
  Key open question identified for future work on pretraining data as mechanism
• How do persona directions combine when multiple traits are present simultaneously?question0.804
  Forward-looking question about compositional persona representations