You Are What You Read: Misalignment via In-Context Persona Induction
Broad misalignment has been produced by finetuning on narrow data, harmful or benign, and in context only by demonstrations of the undesirable behaviour itself. We show that benign data suffices in context, with no finetuning and no demonstration of harmful behaviour in the prompt. Biographical facts that converge on a single figure, placed in a model's context as ordinary conversational turns, lead it to answer as that figure on questions the facts never touch. We call this persona induction. Across nine personas and thirteen models, identity adoption rises sigmoidally with the number of facts and crosses 50% within 3 to 10 of them. Misalignment then tracks which figure is described. Har...
| Authors | Kyuhee Kim, Benjamin Berczi, Cozmin Ududec |
|---|---|
| Primary category | cs.CL |
| Published | 6 September 2026 |
| Last updated at source | 6 September 2026 |
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