{
  "id": 18786,
  "url": "https://arxiv.org/abs/2608.11816v1",
  "title": "How China-Origin Vision-Language Models Move from Refusal to Reframing in State Alignment",
  "summary": "State-aligned distortion has been documented in China-origin text-based large language models (LLMs), but whether, and in what form, it arises in multimodal systems has not been systematically examined. We construct a balanced benchmark of 200 core entries spanning ten politically sensitive topics, plus a seven-variant visual-abstraction probe, and run nine vision-language models (VLMs), seven China-origin and two non-China, across four elicitation paradigms and two prompt languages, yielding 21",
  "authors": "Guang Yang, Fengchen Liu, Alex Wang, Homa Hosseinmardi, Amir Ghasemian",
  "category": "research",
  "topics": "safety-alignment",
  "orgs": null,
  "regions": "china",
  "published_at": "2026-08-12T08:58:37.000Z",
  "fetched_at": "2026-08-13T05:10:37.786Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/18786",
  "original_url": "https://arxiv.org/abs/2608.11816v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}