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RL-trained classifiers can significantly disrupt gradient-based adversarial attacks by rendering gradient information unreliable and ineffective.
Achieve up to 77.5% reduction in semantic alert delay and 98.33% visual evidence delivery within 0.5s by intelligently cascading small and large models and adaptively transmitting data in edge-cloud MLLM systems.
