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The Regime-Enhanced Intelligent Granger Network is proposed, a novel causal discovery framework specifically engineered for nonstationary time series and achieves an Optimal F1 score of 0.529, substantially outperforming PCMCI+ and PC in structural edge recovery.
Compositional Attack Path Scoring (CAPS), a framework engineered to quantify end-to-end multi-hop risks in LLM architectures, establishes a rigorous benchmark for quantitative vulnerability management in complex, agentic LLM environments.
Results indicate that decoupling behavioural signatures from adversarial social positioning is valuable for modern bot detection, and that combining accuracy with interpretable evidence supports deployment in real-world moderation settings.
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