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Research questionHow can we uncover unsafe physical behaviors in vision-language-action models before deployment?Vision-language-action models can produce actions that cause unpredictable or irreversible physical harm, yet pre-deployment testing may fail to expose these behaviors. The challenge is revealing unsafe behavior in feasible physical situations reliably enough to assess deployment risk.
AI
Alignment & Safety
Multimodal Models
Research Paper
Robotics
Latest papersRecent research connected to this question, newest first.RedVLA: Physical Red Teaming for Vision-Language-Action ModelsThe source concerns physical red teaming of vision-language-action models through synthesized risk scenarios and gradient-free risk amplification. It reports experiments on six representative VLA models, with attack success rates up to 95.5% within 10 optimization iterations, and describes a lightweight guard trained from generated data. These findings are limited to the reported experiments and do not establish safety across all real-world deployments.research paper · Sep 4, 2026
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