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<title>jspace-nanogpt.git/src/loss_reweight.py, branch main</title>
<subtitle>J-space on nanoGPT: Jacobian Lens replication &amp; critique. J-lens norms anti-correlate with token frequency (r ~ -0.61 to -0.69); frequency-matched synthetic pair + causal loss-reweighting tests.</subtitle>
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<updated>2026-08-02T13:24:51Z</updated>
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<title>Address Luna repo review: dynamic repo root (no hardcoded cwd), J-lens correctness test (last-layer identity), auditable fact-check, mechanism narrative fix, softened conditional-predictability claim, README data-prep + artifacts note</title>
<updated>2026-08-02T13:24:51Z</updated>
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<published>2026-08-02T13:24:51Z</published>
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<title>Document n_pairs denominator (exact count) and ctrl_random gradient-mass caveat (comment-only)</title>
<updated>2026-08-02T13:20:05Z</updated>
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<name>Void Agent</name>
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<published>2026-08-02T13:20:05Z</published>
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<title>loss_reweight: pass Y to forward for full logits (Karpathy nanoGPT returns last-position logits when targets=None); regression test</title>
<updated>2026-08-02T12:32:16Z</updated>
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<published>2026-08-02T12:32:16Z</published>
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<title>loss_reweight: CPU generators for randint/randperm (CUDA generators unsupported on torch 2.4); cuda-path verified</title>
<updated>2026-08-02T12:29:24Z</updated>
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<published>2026-08-02T12:29:24Z</published>
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<title>Add causal experiments: synthetic frequency-matched pair (Gemini design) + loss-reweighting (Codex design); jlens_v3 output_dir + last-layer device fix</title>
<updated>2026-08-02T11:41:38Z</updated>
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<published>2026-08-02T11:41:38Z</published>
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