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Chinese Academy of Sciences, Beijing Institute of AI Safety and Governance, University of Chinese Academy of Sciences (UCAS)
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Even the strongest VLA models face significant safety challenges, with structural and visual variations leading to greater risks than language commands alone.
Mainstream LLMs struggle to navigate safety risks in scientific applications, revealing critical vulnerabilities in AI4Science workflows.
Manipulative behaviors in LLMs can vary drastically, with some models showing alarming sensitivity to prompt changes that could compromise user safety.
