How does different post-training data shift a model's position along persona dimensions?

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

• post-training steers models toward a particular region of persona space but only loosely tethers them to itquote0.864
  Load-bearing summary of the paper's core finding about persona stability
• Post-training steers models toward a particular region of persona space but only loosely tethers them to it, motivating work on training and steering strategies that more deeply anchor models to a coherent personaclaim0.846
  Central interpretive claim and motivation for future work
• Post-training elicits rather than installs personas; the persona direction is already laid down in pretrainingclaim0.835
  Authors' interpretive endorsement of PSM view, backed by transfer experiments
• 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 behaviorclaim0.829
  The paper's central mechanistic explanation of why narrow fine-tuning causes broad misalignment
• What dimensions of persona are not captured by our extracted role vectors, and how complete is the current persona space mapping?question0.806
  Limitation question motivating future work on persona elicitation strategies
• Projection difference better captures training data influence on persona than raw projection because it accounts for the base model's natural response tendenciesclaim0.805
  Author's interpretive explanation for why projection difference outperforms raw projection in data screening
• Persona representations originate in pretraining, not alignment; they form without explicit supervision as useful features for next-token predictionclaim0.801
  Core interpretive claim providing mechanistic explanation for early persona formation
• There may exist a natural 'persona basis' characterizing the space of all model personas, with correlations between persona vectors predicting co-expression of traitshypothesis0.801
  Open question proposed by authors for future work on the dimensionality and structure of persona space