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arXiv· arXiv:2605.00689· Yunhan Zhao, Zhaorun Chen, Xingjun Ma, Bo Li·Indexed by this site · Originally published

BabelSafe: A policy-grounded multilingual LLM safety benchmark

BabelSafe: A Policy-Grounded Multilingual Safety Benchmark for LLMs

AI summary

BabelSafe is a multilingual LLM safety benchmark covering 13 language environments, with risk categories and rules extracted from regulatory documents of various regions. The paper also proposes BabelGuard, a guardrail model based on a diffusion large language model, with a 1.5B version for fast safe/unsafe classification and a 7B version supporting customizable policy-conditioned safety checks. It performs strongly against 11 guardrail baselines on 6 multilingual safety benchmarks and BabelSafe.

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