diff options
| -rw-r--r-- | RESIDUAL_MIRROR.md | 23 | ||||
| -rw-r--r-- | RESULTS.md | 15 | ||||
| -rw-r--r-- | REVIEW_SCORECARD.md | 2 | ||||
| -rw-r--r-- | ROADMAP.md | 9 | ||||
| -rw-r--r-- | results/residual_mirror_short/rrm_lr0.03.json | 756 | ||||
| -rw-r--r-- | results/residual_mirror_short/rrm_lr0.1.json | 756 | ||||
| -rw-r--r-- | results/residual_mirror_short_gate.json | 77 |
7 files changed, 1638 insertions, 0 deletions
diff --git a/RESIDUAL_MIRROR.md b/RESIDUAL_MIRROR.md index 61e5691..ab13eb8 100644 --- a/RESIDUAL_MIRROR.md +++ b/RESIDUAL_MIRROR.md @@ -95,3 +95,26 @@ rate and observation count, residual mirroring improves early alignment by `0.038200`. This is evidence that removing estimator noise at the fixed point matters. It remains inherited local predictive weight estimation, so the strict reviewer score stays `5/10`. + +## Audited RRM-2 outcome + +The frozen short accuracy gate passed on source revision `6206483`: + +| hidden LR | validation accuracy | early alignment | all-layer alignment | feedback/forward cosine | +|--:|--:|--:|--:|--:| +| 0.03 | 62.32% | 0.999604 | 0.999692 | 0.999970 | +| 0.10 | **65.08%** | **0.999128** | **0.999377** | **0.999902** | + +The accuracy selector chooses hidden LR 0.1. It clears the 65% gate by only +0.08 points and lies 9.86 points below matched BP at 74.94%, clearing the +within-10-point gate by 0.14 points. Both runs are finite. The selected run +uses zero task-loss queries, 119 mirror events, `2.4256703e13` MACs +(`0.9969x` matched BP), 1.731 GB peak allocated memory, and 93.0 s on a GTX +1080. Every frozen RRM-2 check passes, so RRM-3 opens without changing the +selected mirror rate, cadence, or hidden learning rate. + +The nearly exact directional and weight cosines do not erase the short-horizon +accuracy gap. This makes the result more useful as a strict baseline: direction +alone is not a surrogate for trajectory equivalence, especially when feedback +tracks changing forward weights at discrete intervals. Because RRM is inherited +predictive weight estimation, this pass does not change the reviewer score. @@ -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>`. diff --git a/REVIEW_SCORECARD.md b/REVIEW_SCORECARD.md index 33ffb4e..e9eae6a 100644 --- a/REVIEW_SCORECARD.md +++ b/REVIEW_SCORECARD.md @@ -65,6 +65,7 @@ Every formal result report records: | Normalized response mirror capture passes | 5 | Twenty local observations reach 0.446 early alignment and 0.915 feedback/forward cosine at zero task-loss queries | Strongly resolves the engineering bottleneck, but all credit belongs to an inherited weight-estimation baseline until innovation is load-bearing | | Normalized response mirror short gate fails | 5 | WM reaches 64.04% and 0.939 early alignment at 0.9968x BP MACs, but misses its two accuracy gates by under one point | Strong inherited baseline and useful warning that alignment is insufficient; full run and any SDIL scale claim remain closed | | Residual response mirror capture passes | 5 | RRM reaches 0.665 early and 0.730 all-layer alignment with 0.954 feedback/forward cosine after 20 zero-query local observations | Opens the frozen short accuracy gate, but remains inherited predictive weight estimation rather than SDIL evidence | +| Residual response mirror short gate passes | 5 | RRM reaches 65.08%, within 9.86 points of matched BP, at 0.9969x BP MACs and nearly exact alignment | Opens one full validation run; the inherited baseline still supplies no Harnett-specific evidence | | Oral-A A4 | not opened | The prerequisite A3 gate failed | No oral-A confirmation claim is available | These are conditional reviewer forecasts, not promised scores. A failed stage leaves its negative @@ -88,6 +89,7 @@ retroactively reopened by success on standard vision benchmarks. | 2026-07-22 / response-mirror WM-1 | Four clean frozen-forward records; selected etaM 0.1 reaches 0.4461 early and 0.5422 all-layer alignment with zero task-loss queries | 5 → 5 | Opens a strong inherited-baseline accuracy test and isolates information source as the bottleneck, but supplies no Harnett-specific task evidence | | 2026-07-22 / response-mirror WM-2 | Two clean short ResNet records; selected WM reaches 64.04% with 0.9393 early alignment and 0.9968x BP MACs, missing both accuracy gates narrowly | 5 → 5 | Substantially strengthens the comparator and cost story, but closes its full run and demonstrates that high credit cosine alone is not a scale result | | 2026-07-22 / residual response-mirror RRM-1 | Four frozen-forward records; selected etaM 0.1 reaches 0.6651 early and 0.7303 all-layer alignment with controlled norms, zero task-loss queries, and 2.4458e9 MACs | 5 → 5 | Residual prediction removes much of the fixed-point estimator noise and opens the short task gate, but the gain belongs to an inherited baseline and does not establish somato-dendritic innovation | +| 2026-07-22 / residual response-mirror RRM-2 | Two clean short ResNet records; selected RRM reaches 65.08%, 9.86 points below BP, with 0.9991 early alignment and 0.9969x BP MACs | 5 → 5 | Narrowly opens the full baseline run and strengthens the efficient comparator; the remaining accuracy gap despite near-exact direction warns that alignment is not trajectory equivalence | Future rows are appended only after an audited frozen stage. A score staying flat is informative: engineering, theory exposition, or visualization may make the paper more defensible without @@ -438,6 +438,15 @@ rate is not widened or retuned. The frozen two-rate RRM-2 short accuracy screen is opened. This is inherited baseline progress and cannot change the paper score until a load-bearing innovation experiment uses the substrate. +**Residual response-mirror RRM-2 status: short accuracy gate passed +narrowly.** Selected hidden LR 0.1 reaches `65.08%`, 9.86 points below matched +BP at `74.94%`, with early/all alignment `0.999128/0.999377`, feedback/forward +cosine `0.999902`, zero task-loss queries, and `0.9969x` BP MACs. It clears the +two accuracy margins by only 0.08 and 0.14 points; the LR-0.03 run reaches +62.32%. Every frozen check nevertheless passes, so exactly one RRM-3 full +validation run opens at the selected settings. The result remains baseline +evidence and the reviewer score stays 5/10. + 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 diff --git a/results/residual_mirror_short/rrm_lr0.03.json b/results/residual_mirror_short/rrm_lr0.03.json new file mode 100644 index 0000000..a11eafb --- /dev/null +++ b/results/residual_mirror_short/rrm_lr0.03.json @@ -0,0 +1,756 @@ +{ + "architecture": { + "adaptive_apical_parameters": 0, + "adaptive_feedback_parameters": 267904, + "base_width": 16, + "blocks_per_stage": 3, + "bn_eps": 1e-05, + "bn_momentum": 0.1, + "depth": 20, + "family": "CIFAR 6n+2 ResNet, option-A shortcuts", + "fixed_feedback_parameters": 0, + "fixed_traffic_coefficients": 0, + "forward_parameters": 269722, + "hidden_shapes": [ + [ + 16, + 32, + 32 + ], + [ + 16, + 32, + 32 + ], + [ + 16, + 32, + 32 + ], + [ + 16, + 32, + 32 + ], + [ + 16, + 32, + 32 + ], + [ + 16, + 32, + 32 + ], + [ + 16, + 32, + 32 + ], + [ + 32, + 16, + 16 + ], + [ + 32, + 16, + 16 + ], + [ + 32, + 16, + 16 + ], + [ + 32, + 16, + 16 + ], + [ + 32, + 16, + 16 + ], + [ + 32, + 16, + 16 + ], + [ + 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