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State information in LLM-driven agents can be exploited, turning their task execution capabilities into a potential attack surface.
Context-augmented RL lets smaller MLLMs punch *way* above their weight, rivaling much larger models on reasoning tasks while dodging reward hacking.
AgentSentry stops indirect prompt injection attacks in LLM agents by pinpointing when the attack takes hold using causality, then surgically removing the malicious influence.
