Tracing Persona Vectors Through LLM Pretraining
How large language models internally represent high-level behaviors is a core interpretability question with direct relevance to AI safety: it determines what we can detect, audit, or intervene on. Recent work has shown that traits such as evil or sycophancy correspond to linear directions in the internal activations, the so-called persona vectors. Although these vectors are now routinely utilized to inspect and steer model behavior in safety-relevant settings, how these representations are formed during training remains unknown. To address this gap, we trace persona vectors across the pretraining of OLMo-3-7B, finding that persona vectors form remarkably early -- within 0.22% of OLMo-3 p...
| Authors | Viktor Moskvoretskii, Dominik Glandorf, Jorge Medina Moreira et al. |
|---|---|
| Primary category | cs.CL |
| Published | 13 May 2026 |
| Last updated at source | 13 May 2026 |
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