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A1: 240 rows (3 alpha × 2 depth × 4 methods × 10 seeds)
A2: 30 rows (3 methods × 10 seeds)
naive_StateErr = ||h_{L//2} - h_L|| / ||h_L||
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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A1: Synthetic nonlinearity ladder (240 rows: 3 alpha × 2 depth × 4 methods × 10 seeds)
A2: CIFAR state-vs-credit counterexample (30 rows: 3 methods × 10 seeds)
A3: Frozen vs online dissociation (60 rows: 2 regimes × 3 methods × 10 seeds)
A4: Protocol dependence panel (82 rows: assembled from existing results)
All experiments ran on GPU 3. Total runtime: ~20 hours.
CSVs in results/confirmatory/.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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All experiments complete:
- Toy LQ: credit bridge matches state bridge (~0.94 costate cosine)
- CIFAR-10: credit bridge (29.6%) comparable to DFA (30.0%), both beat state bridge (18.5%)
- State bridge confirms core hypothesis: perfect state prediction != useful credit
- Terminal gradient matching is essential for credit bridge
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Debug phase. Toy LQ experiments (3 seeds) complete with terminal gradient matching.
Credit bridge matches state bridge on linear system (~0.94 cosine).
CIFAR experiments in progress.
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