| Age | Commit message (Collapse) | Author |
|---|
|
- CIFAR deltaL: s=grad_hL CE (dim=512) -> acc=17.2%, Gamma≈0
Confirms scalar value field has dimensionality bottleneck on CIFAR
- Pivot memo: direct vector credit field a_phi(h,t,s) -> R^d
Trained with perturbation-based target, avoids curvature problem
Still satisfies no hidden BP anchor constraint
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
|
|
CIFAR gap
Three new plots:
- cifar_depth_scan.png: acc/Gamma/rho vs depth for all methods
- boundary_ablation.png: s_type, tgw, warmup ratio sweeps
- synth_vs_cifar.png: dimensionality gap comparison (d=128 vs d=512)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
|
|
Key findings:
- deltaL (output-layer gradient) gives best Gamma (0.562 vs 0.452 for eT)
- Concatenating h_L to s destroys credit quality (value net cheats)
- Terminal gradient matching is monotonically beneficial
- Best config: deltaL + tgw=1.0 + wr=0.05 -> Gamma=0.768, rho=0.691
- CIFAR depth scan shows no Goldilocks regime (dimensionality bottleneck)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
|
|
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>
|
