arXiv:2610.09708v1 Announce Type: new Abstract: Vision-Language-Action models (VLAs) are increasingly deployed in safety-critical physical environments, yet their adversarial robustness remains poorly understood. Existing attacks typically assume white-box access or rely on surrogate VLAs, which rarely holds in real-world deployments.
Black-Box Adversarial Patch Attacks on VLAs via Ancestor VLM Exploitation
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