AI Research
Safety Beyond the Interface: Detecting Harm via Latent States in Large Language Models
Moving AI safety inside the model architecture to eliminate latency and improve real-time security.
Autonomous systems increasingly rely on Large Language Models (LLMs) yet the safety infrastructure surrounding these models introduces latency and compute overhead. This limits utility in resource-constrained, time-critical deployments. Existing external guardrail models remain b...
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ArXiv CS.AI
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ArXiv CS.AI
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Generated insight by OnAirToday AI
Monitoring latent states allows for high-performance safety detection that bypasses the computational latency of external guardrail models. This research provides a pathway for deploying secure autonomous systems in time-critical environments where traditional filtering methods are too slow.
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