LPG: Balancing Efficiency and Policy Reasoning in Latent Policy Guardrails
Guardrails are a critical safety layer for modern AI systems, but their operating regime is changing. As LLMs are deployed as customized assistants, safety policies are increasingly specified at inference time by users, organizations, or regulatory contexts. This makes safety enforcement fundamentally dynamic: the guardrail should adapt to changing safety policies without retraining. Yet this requirement creates a fundamental tension: faithfully judging complex policy contexts demands reasoning capability, while practical deployment requires low-latency responses. We introduce Latent Policy Guardrail (LPG), a guardrail framework that learnssemantic latent deliberation over dynamic policie...
| Authors | Nanxi Li, Zhengyue Zhao, Chaowei Xiao |
|---|---|
| Primary category | cs.CR |
| Published | 17 May 2026 |
| Last updated at source | 17 May 2026 |
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