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MIDS outperforms existing intrusion detection systems by over 8 percentage points in detecting stealthy masquerade attacks on vehicle networks.

Resource-level supervision boosts Website Fingerprinting accuracy by over 8% even under significant temporal drift, challenging the limitations of traditional low-level feature reliance.

LLMs struggle with Office automation, scoring only 36.6% on a standardized proficiency exam, revealing a critical gap in their capabilities.

LLMs can orchestrate existing static analysis tools to achieve state-of-the-art Android malware detection at a fraction of the cost, without any domain-specific fine-tuning.