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LLMs can get a 27.8% boost in mathematical reasoning by fusing a hardware-efficient optimal control layer directly into their architecture, enabling planning before prediction.
Forget scaling bottlenecks: DG-PG uses differentiable analytical models to slash gradient variance in cooperative MARL, achieving convergence in a 200-agent cloud scheduling task where standard methods fail.
