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authorYurenHao0426 <Blackhao0426@gmail.com>2026-03-23 22:29:08 -0500
committerYurenHao0426 <Blackhao0426@gmail.com>2026-03-23 22:29:08 -0500
commit13668ac1050fee1fa84067fa07c5eaab1a1bc939 (patch)
tree40f881857938cd5f91c881b221f24a074b185033 /NOTE.md
parent9940a5e2d3a45fc97eba33fd504bf7b1123a50ab (diff)
Add Phase 1 synthetic ladder results and memo
Key finding: credit bridge advantage scales with nonlinearity. At alpha=1.0 (full tanh), CB > SB > DFA on both Gamma and rho at all depths. The crossover where CB surpasses SB happens around alpha=0.7-1.0. Full 4x4x3 grid complete with 3 seeds each. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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- **pilot**: Controlled iteration (commits 0b9ebb2, 7baf7ae)
- **frozen**: Code at commit 0b9ebb2 for all reported results
-## Status: COMPLETE
+## Status: PHASE 2 EXPLORE IN PROGRESS
---
@@ -70,3 +70,56 @@
2. DFA warmup for credit bridge (20% of epochs): prevents value net bootstrap failure
3. Normalized MSE for state bridge: numerical stability
4. Credit normalization: a_norm = a / (RMS(a) + 1e-6)
+
+---
+
+## Phase 2: Explore (commit 2403960+)
+
+### Synthetic Nonlinearity Ladder (Phase 1 of explore)
+
+**Setup**: Teacher-student with phi_alpha(z) = (1-alpha)*z + alpha*tanh(z)
+- alpha in {0, 0.25, 0.5, 1.0}, L in {2, 4, 8, 12}
+- d=128, C=10, 80 epochs, 3 seeds
+
+**Critical Finding**: Credit bridge advantage scales with nonlinearity.
+
+At alpha=1.0 (full tanh), credit bridge is the BEST method on Gamma and rho at ALL depths:
+
+| L | DFA Gamma | SB Gamma | CB Gamma | DFA rho | SB rho | CB rho |
+|---|-----------|----------|----------|---------|--------|--------|
+| 2 | 0.03 | 0.52 | **0.53** | 0.03 | 0.47 | **0.57** |
+| 4 | 0.05 | 0.34 | **0.45** | 0.06 | 0.32 | **0.51** |
+| 8 | 0.06 | 0.25 | **0.36** | 0.07 | 0.23 | **0.42** |
+| 12 | 0.07 | 0.22 | **0.24** | 0.07 | 0.21 | **0.32** |
+
+At alpha=0.5 (moderate nonlinearity), SB still wins on Gamma but CB wins on rho at L=4.
+At alpha=0 (linear), SB dominates.
+
+**Interpretation**: State bridge fails via Jacobian mismatch, not value prediction error.
+Credit bridge avoids this by learning value field gradients directly.
+The crossover happens around alpha=0.7-1.0.
+
+### CIFAR-10 Depth Scan (Phase 2 of explore, in progress)
+
+Sweep L={2,4,6,8,12}, d=512, 100 epochs on CIFAR-10.
+Preliminary results (L=2,4, seed=42):
+
+| L | Method | Acc | Gamma | rho |
+|---|--------|-----|-------|-----|
+| 2 | DFA | 0.312 | 0.196 | 0.001 |
+| 2 | CB | 0.311 | 0.175 | **0.031** |
+| 4 | DFA | 0.314 | 0.100 | 0.003 |
+| 4 | CB | 0.298 | 0.123 | -0.002 |
+
+CIFAR is much harder -- rho signal is very weak for all non-BP methods.
+
+### Changes Log (explore phase)
+- `2403960`: Add synthetic ladder and CIFAR depth scan experiments
+- Student blocks now use pre-LayerNorm for stability (fixes L>=8 blowup)
+- Added gradient clipping to block updates
+
+### Experiment IDs (explore phase)
+- `synth_ladder_smoke/`: Initial 3-alpha x 2-depth smoke test
+- `synth_ladder_v2_lo/`: Full alpha=0,0.25 x L=2,4,8,12 x 3 seeds
+- `synth_ladder_v2_hi/`: Full alpha=0.5,1.0 x L=2,4,8,12 x 3 seeds
+- `cifar_depth_scan_s42/`: CIFAR L=2,4,6 x d=512 x seed=42 (in progress)