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@@ -783,6 +783,29 @@ The next comparator must change the information source rather than reopen the
rate/query grid, for example local response-based learned FA or weight
mirroring. No test endpoint was evaluated.
+### Normalized local response mirror capture
+
+The inherited normalized response-mirror baseline changes exactly that
+information source. A Gaussian parent probe passes through the local forward
+synapses, while a separate Q/R update consumes only parent/child activities.
+The frozen CIFAR-prefix WM-1 screen gives:
+
+| method/rate | early alignment | all-layer alignment | feedback/forward cosine | norm range |
+|:--|--:|--:|--:|:--|
+| fixed HFA | -0.000263 | 0.011279 | 0.001614 | [0.959, 1.055] |
+| WM 0.03 | 0.075263 | 0.235197 | 0.625186 | [0.697, 0.787] |
+| WM 0.10 | **0.446141** | **0.542159** | **0.915480** | **[0.889, 1.157]** |
+| WM 0.30 | 0.112177 | 0.228114 | 0.853343 | [0.999, 1.697] |
+
+All five frozen checks pass at selected `eta_M=0.1`. Twenty batch-1 local
+observations cost `1.6305e9` MACs and consume zero task-loss queries, only
+`0.0067%` of the fixed-HFA short screen's `2.4242e13` MACs. This sharply
+separates the previous failures: the hierarchical feedback family is usable
+and cheap to identify from vector-valued local responses, whereas 800 global
+task-scalar queries did not calibrate it. WM-2 therefore opens. The result is
+credited entirely to an inherited weight-estimation baseline; it cannot raise
+the SDIL novelty score by itself.
+
## 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>`.