Disentangling Intent from Role: Adversarial Self-Play for Persona-Invariant Safety Alignment
The growing capabilities of large language models (LLMs) have driven their widespread deployment across diverse domains, even in potentially high-risk scenarios. Despite advances in safety alignment techniques, current models remain vulnerable to emerging persona-based jailbreak attacks. Existing research on persona-based jailbreak has primarily focused on attack iterations, yet it lacks systemic and mechanistic constraints on the defense side. To address this challenge, we propose Persona-Invariant Alignment (PIA), an adversarial self-play framework that achieves co-evolution through Persona Lineage Evolution (PLE) on the attack side and Persona-Invariant Consistency Learning (PICL) on t...
| Authors | Jiajia Li, Xiaoyu Wen, Zhongtian Ma et al. |
|---|---|
| Primary category | cs.AI |
| Published | 3 May 2026 |
| Last updated at source | 3 May 2026 |
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