PL-Guard: Probabilistic Logic Reasoning for LLM Guardrails
Large language model guardrails can be viewed as policy-consistency problems: a system must determine which policy-relevant facts hold in a prompt-response pair and what those facts imply under a given policy. Common approaches, including policy prompting and LLM-as-a-judge pipelines, often overlap the tasks of semantic grounding and policy reasoning: the model both interprets the prompt-response pair and reasons about whether a policy has been violated. This can lead to unsafe compliance with harmful prompts, or refusals to assist benign ones. To separate grounding and reasoning roles, we propose PL-Guard, a neurosymbolic guardrail architecture. Using a symbolic policy interface consisti...
| Authors | Satchit Chatterji, Shihan Wang, Giovanni Sileno et al. |
|---|---|
| Primary category | cs.LG |
| Published | 16 August 2026 |
| Last updated at source | 16 August 2026 |
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