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@@ -853,6 +853,21 @@ RRM-2 is opened using the already frozen rate and cadence. This is a strong inherited learned-alignment baseline, not Harnett-specific evidence, so it does not raise the SDIL paper score by itself. +The frozen RRM-2 short task gate subsequently passes: + +| method | validation accuracy | early alignment | all-layer alignment | estimated MACs | +|:--|--:|--:|--:|--:| +| RRM, hidden LR 0.03 | 62.32% | 0.999604 | 0.999692 | 2.4257e13 | +| RRM, hidden LR 0.10 | **65.08%** | **0.999128** | **0.999377** | 2.4257e13 | +| matched BP | 74.94% | n/a | n/a | 2.4331e13 | + +The selected run clears 65% by 0.08 points and the within-10-point BP gate by +0.14 points. It is finite, uses zero task-loss queries, costs `0.9969x` matched +BP MACs, and retains feedback/forward cosine `0.999902`. All frozen checks pass, +so the single RRM-3 full validation run opens. The 9.86-point gap despite nearly +perfect instantaneous alignment is retained as a negative diagnostic rather +than treating cosine as a proxy for optimization equivalence. + ## How to run `experiments/run.py --mode {bp,fa,dfa,sdil} --dataset {mnist,fmnist,cifar10} --depth D --residual {0,1} --act {tanh,gelu,silu,relu}` Batteries: `experiments/run_v2.sh <ds> "<depths>" <res> <act> "<seeds>" <ep> <pfx>`. |