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A replay-regularized, attack-aware curriculum that steps exposure based on measured attack influence is proposed that shows improved overall robustness and reduced attack-level imbalance compared with standard multi-attack training.
Disagreement-triggered escalation can blind multi-agent systems to critical failures, but ARAT shows how to turn this risk into a safety advantage.
