TAKO demonstrates real-time adversarial takeover of robotic diffusion policies via reusable universal patches on visual inputs, achieving 100% success in steering attacker-chosen trajectories across multiple tasks, encoders, and diffusion methods.
arXiv preprint arXiv:2410.13691 (2024)
5 Pith papers cite this work. Polarity classification is still indexing.
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A unified threat model for LLM-enabled robots reveals three cross-boundary attack chains from user input to unsafe physical actuation due to missing validations and unmediated crossings.
Empirical study finds LLM robustness to sensory prompt injections in robotic systems is model-specific rather than scale-dependent, with a hybrid firewall blocking known patterns but bypassed by obfuscated variants at 10.2% rate.
Non-model gains via inference, systems, and assets can drive AI capabilities independently of base models, requiring governance beyond model-level evaluation and mitigation.
A literature review of pHHI that proposes a taxonomy of interaction types by modality and engagement level while outlining pathways to integrate control, intent, and modeling for more seamless humanoid-human collaboration.
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Comprehensive AI governance requires addressing non-model gains
Non-model gains via inference, systems, and assets can drive AI capabilities independently of base models, requiring governance beyond model-level evaluation and mitigation.