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authorYurenHao0426 <Blackhao0426@gmail.com>2026-07-27 14:51:17 -0500
committerYurenHao0426 <Blackhao0426@gmail.com>2026-07-27 14:51:17 -0500
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figure: audit standard-depth SDIL scaling
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+# Standard-depth ResNet scaling figure caption
+
+**Figure 6 | Dynamic somato-dendritic innovation scales across standard
+ResNet depth.** All points are frozen CIFAR-10 test endpoints from seeds
+10--14 after 200 epochs; error bars show 95% normal intervals over paired
+seeds. The renderer validates all 60 records and their source hashes against
+the passed predeclared gate. **a,** BP, clean reciprocal Kolen--Pollack credit,
+and dynamic SDIL under four-times-RMS soma-predictable apical traffic all gain
+accuracy from ResNet-20 to ResNet-56. SDIL gains 1.176 points, and all five
+paired seeds improve. **b,** On the full accuracy scale, fixed direct feedback
+alignment remains far below both reciprocal local learners at every depth;
+the complete nine-method crossover is reported separately rather than inferred
+from this four-method panel. **c,** Paired ResNet-56 minus ResNet-20 gains for
+BP and SDIL. **d,** SDIL retains a mean early-third teaching-signal cosine
+above 0.9994 while its hardware-independent affine-MAC estimate remains below
+1.34 times matched BP. Exact gradients are diagnostic-only and never used for
+learning. The SDIL rule uses no task-loss queries but does use one explicitly
+counted instruction-off neutral observation per ordinary example.