This is a Stage-B research weight release: three trained input hidden→hidden Rank-4 LRARC slow initializations (rho), together with the original, always-enabled semantic adapter omega. The exact MiniCPM5-1B-SFT backbone must be obtained separately. This is a finite four-program selection policy, not a standalone chat model or a completed PDSA system. 中文：本目录保存 B 阶段选定静态目标臂的三个训练后 rho 和必需的原 omega。三种子整体保留，未挑最好的一次。A/B 已完成本轮验收；权威记忆、预测写入 Q、双状态联合效应和严格 RSI 尚未由这些权重验证。 Junyi Zou and Avrova Donz. MMLA: Memory-Mediated Learning Architecture for Predictive Dual-State Adaptation, arXiv:2606.28876v4, 2026. MMLA is a mixer-agnostic learning architecture. Its identity is not defined by the temporarily reused…