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authorYurenHao0426 <Blackhao0426@gmail.com>2026-04-08 05:47:47 -0500
committerYurenHao0426 <Blackhao0426@gmail.com>2026-04-08 05:47:47 -0500
commit52693a9be4349c2820ac79e3e3d9af53813a7412 (patch)
treea198bbd855bce25b6a37fb730eb8de1fc3e29765 /results/confirmatory/cifar_d512/dfa_s456.json
parent8dd65b2ec3df32749adabbf62c55101d5b00ae7b (diff)
Round 34 random-target ablation: Mode 1 fires under random labels too
Codex round 34 picked OPTION A (i.i.d. random class targets per minibatch) over the analytic-only OPTION D as the most discriminating test of 'is (a) intrinsic to DFA update geometry or task-driven?'. Smoke test result is unambiguous: ep 0: ||h_L||=8.9 ||g_L||=9.8e-4 ep 1: ||h_L||=1616 ||g_L||=5.1e-6 ep 2: ||h_L||=9768 ||g_L||=8.5e-7 ep 3: ||h_L||=14510 ||g_L||=5.6e-7 (test acc still at chance ~0.07) Three orders of magnitude growth in ||h_L|| in 3 epochs, three orders of magnitude collapse in ||g_L|| in the same 3 epochs, with NO task signal whatsoever — DFA's local-loss geometry is the proximate driver, not data adaptation. - experiments/snapshot_evolution_residual_explosion.py: add --random_targets and --skip_bp flags - paper/main.tex §3 ¶1: replace 'no explicit scale constraint' framing with codex round 34's 6-line geometric argument and the random-target empirical falsifier - paper/main.tex Appendix J: full smoke-test table + interpretation - v2.3: 14 pages total, main content still 8 pages Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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