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System Intelligence emerges as a game-changer, enabling LLM agents to collaborate effectively across complex tasks by organizing their interactions through dynamic graph structures.
SIRLM significantly boosts the reasoning fidelity of LLMs in Knowledge Graph tasks, outperforming existing methods by tightly coupling structural knowledge with parametric learning.
TFR-Net not only prevents knowledge re-emergence during continual unlearning but also enhances model capacity, achieving a remarkable trade-off between unlearning and utility retention.
