From 9763a8ecf4d614370cfde3ff926c5070ab766433 Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Wed, 22 Jul 2026 12:19:44 -0500 Subject: baselines: complete native author-code audit --- RESULTS.md | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) (limited to 'RESULTS.md') diff --git a/RESULTS.md b/RESULTS.md index 5ef402a..6b11b34 100644 --- a/RESULTS.md +++ b/RESULTS.md @@ -586,6 +586,25 @@ strong modern EP variant remains necessary. DFA is also strong on easy MNIST, so comes from the five-depth CIFAR panel; this comparison establishes that SDIL need not trade away accuracy to obtain a large cost advantage over canonical EP. +### Native author-code CIFAR-10 baselines + +These are executable-fidelity reproductions under the authors' architectures +and schedules, not equal-compute comparisons with SDIL: + +| method | reproduced seed | primary test (%) | validation-selected test (%) | test-selected test (%) | published (%) | audited wall (s) | +|:--|--:|--:|--:|--:|--:|--:| +| BurstCCN | 0 | 80.070 | 80.100 | 80.250 | 82.97 +/- 0.21 | 15451.3 | +| Dual Prop | 1988 | 92.460 | 92.460 | n/a | 92.41 +/- 0.07 | 23119.8 | + +BurstCCN's primary value is the final epoch and its best-test value is +test-selected because native code evaluates test every epoch. Dual Prop +restores the best-validation checkpoint and evaluates test once, so primary +and validation-selected values coincide. Both strict records include source, +environment, dataset, artifact, selection, and wall-definition audits. Dual +Prop reproduces its published accuracy almost exactly, but uses VGG16 with 16 +nudged inference passes and about 6.42 hours of author-measured compute on a +GTX 1080. + ### Frozen standard-ResNet development funnel The prospective Oral-A funnel used a 45k/5k training-only CIFAR-10 split; no -- cgit v1.2.3