arXiv — NLP / Computation & Language · · 3 min read

Benchmarking LLM Compliance with China AI Generated Content Regulations

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Computer Science > Computation and Language

arXiv:2609.19989 (cs)
[Submitted on 17 Sep 2026]

Title:Benchmarking LLM Compliance with China AI Generated Content Regulations

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Abstract:The widespread adoption of LLMs has led to escalating content compliance risks. Prior works have contributed to addressing these risks in the English context, downplaying the complexity of Chinese language content. This paper follows China's current AI-Generated content compliance requirements and provides evaluation results on 20 notable LLMs, offering insight into China's regulatory landscape. We design a novel framework to assess the compliance and refusal rates with 2303 questions spanning six distinct dimensions, including 203 self-constructed constitutional questions. The framework employs several judges to generate verdicts independently based on their hierarchical alignment memory. Our findings show that international models also exhibit high levels of compliance despite the use of standard Chinese questions, and the main differences may stem from dimensions closely related to ideological alignment. We establish a regulatory benchmark that enables the global AI community to evaluate both Chinese and non-Chinese LLMs under a unified set of legally grounded compliance requirements.
Comments: 5 pages, 3 figures, with appendix still improving
Subjects: Computation and Language (cs.CL); Multiagent Systems (cs.MA)
Cite as: arXiv:2609.19989 [cs.CL]
  (or arXiv:2609.19989v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2609.19989
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Weichao Chen [view email]
[v1] Thu, 17 Sep 2026 09:58:14 UTC (1,663 KB)
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