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| author | YurenHao0426 <Blackhao0426@gmail.com> | 2026-03-26 08:37:39 -0500 |
|---|---|---|
| committer | YurenHao0426 <Blackhao0426@gmail.com> | 2026-03-26 08:37:39 -0500 |
| commit | ef4aed70130e2212b4ed1cb7212e2ea6c7c7adb2 (patch) | |
| tree | ad9f128753350ec4f430f77baa018189e4a9d4be /experiments/__pycache__ | |
| parent | 05ccd23154d1e9d090178b9d4d5f2c821711e784 (diff) | |
Add Phase 10A: no prefit threshold — even random Vec blend beats DFA by +1.3%
E_prefit=0 (random Vec) + blend(0.75): 32.4% vs DFA 31.1% (+1.3%)
E_prefit=15: 32.3% (+1.2%)
E_prefit=60: 32.5% (+1.4%)
Frozen Gamma/rho near zero at all prefit levels. The Phase 9A success was NOT
from Vec learning useful credit — it was from the blend mechanism itself providing
regularization/diversification over pure DFA.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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