From da109afa23146988188c3af910c6a6205f0c63d9 Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Wed, 22 Jul 2026 12:46:08 -0500 Subject: analysis: localize early-layer feedback bottlenecks --- ROADMAP.md | 9 +++++++++ 1 file changed, 9 insertions(+) (limited to 'ROADMAP.md') diff --git a/ROADMAP.md b/ROADMAP.md index 75e606a..2ad919f 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -364,6 +364,15 @@ was not launched; test and confirmation seeds remain untouched. This localizes the remaining bottleneck to early-layer credit rather than merely spatial projection variance. +The subsequent no-training representation oracle further decomposes that +bottleneck. The existing spatial fields reach `0.05494` early alignment with +unconstrained per-example coefficients; the actual output-error-conditioned +family reaches `0.02397` on a disjoint 32-example batch, while learned v2 +reaches `0.00721`. Naive local-average/channel-context fields fall slightly to +`0.02246`. The next algorithmic branch should therefore address both causal +sample efficiency and feedback context; simply lowering `eta_A`, adding the +tested fields, or reopening V2-2 is not justified. + Prepare convolutional local-update primitives and ResNet-20/32/56 protocols early. Queue frozen runs opportunistically on authorized idle GPUs. Because BurstCCN already reports CIFAR-10 and ImageNet scaling, dataset scale alone is not novel. The oral-level target is a memorable joint -- cgit v1.2.3