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<title>World-Alignment.git/LAB_NOTES.md, branch main</title>
<subtitle>Unnamed repository; edit this file 'description' to name the repository.
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<link rel='alternate' type='text/html' href='https://git.blackhao.com/World-Alignment.git/'/>
<entry>
<title>Retire the correlation gate: the shared spectrum governs recovery</title>
<updated>2026-08-01T21:15:41+00:00</updated>
<author>
<name>YurenHao0426</name>
<email>Blackhao0426@gmail.com</email>
</author>
<published>2026-08-01T21:15:41+00:00</published>
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<content type='text'>
A controlled truncation refutes the project's central go/no-go rule.
Projecting the recovering synthetic fields to rank r holds the field
correlation at 0.902-0.929 while recovery moves 6.2% -&gt; 12.9% -&gt; 95.6%
across ranks 4, 8, 16. A field past the supposed 0.9 threshold recovers
13%, so correlation neither predicts nor forbids recovery and the width
of the shared spectrum is what moves it.

The gate becomes a joint condition on correlation and shared width,
measured by principal angles against a scene-shuffled null. Neither
suffices alone: 18 shared directions at 0.508 fails, 11 at 0.902 fails.

With the old gate retired, natural data was finally searched: 0.0000
against 0.0039 chance. The old verdict was right, its reasoning was not.

Also closes route D by measurement. rho_IT ~ sqrt(4 log N / N) rises as N
falls, and at N = 16 through 96 the deepest state a strong searcher
reaches is deeper than the truth in 3/3 replicates at every size.

Free gains: eigenvalue-weighted projection over a wide basis with
128-dim text vectors takes the correlation 0.656 -&gt; 0.716 and shared
width 10 -&gt; 16. Hubness refuted as an inflation hypothesis.

Moving the per-image segmentation eigendecomposition onto the GPU cut
batch time from 130s to 1.9s.

Co-Authored-By: Claude &lt;noreply@anthropic.com&gt;
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<pre>
A controlled truncation refutes the project's central go/no-go rule.
Projecting the recovering synthetic fields to rank r holds the field
correlation at 0.902-0.929 while recovery moves 6.2% -&gt; 12.9% -&gt; 95.6%
across ranks 4, 8, 16. A field past the supposed 0.9 threshold recovers
13%, so correlation neither predicts nor forbids recovery and the width
of the shared spectrum is what moves it.

The gate becomes a joint condition on correlation and shared width,
measured by principal angles against a scene-shuffled null. Neither
suffices alone: 18 shared directions at 0.508 fails, 11 at 0.902 fails.

With the old gate retired, natural data was finally searched: 0.0000
against 0.0039 chance. The old verdict was right, its reasoning was not.

Also closes route D by measurement. rho_IT ~ sqrt(4 log N / N) rises as N
falls, and at N = 16 through 96 the deepest state a strong searcher
reaches is deeper than the truth in 3/3 replicates at every size.

Free gains: eigenvalue-weighted projection over a wide basis with
128-dim text vectors takes the correlation 0.656 -&gt; 0.716 and shared
width 10 -&gt; 16. Hubness refuted as an inflation hypothesis.

Moving the per-image segmentation eigendecomposition onto the GPU cut
batch time from 130s to 1.9s.

Co-Authored-By: Claude &lt;noreply@anthropic.com&gt;
</pre>
</div>
</content>
</entry>
<entry>
<title>Landscape reshaping does not substitute for field correlation</title>
<updated>2026-08-01T19:45:16+00:00</updated>
<author>
<name>Yuren Hao</name>
<email>blackhao0426@gmail.com</email>
</author>
<published>2026-08-01T19:45:16+00:00</published>
<link rel='alternate' type='text/html' href='https://git.blackhao.com/World-Alignment.git/commit/?id=58b9c84dae293359f498fdf6afd533df5c9d3c25'/>
<id>58b9c84dae293359f498fdf6afd533df5c9d3c25</id>
<content type='text'>
A rank-truncation ladder from four to full rank returns chance accuracy
at the natural-data correlation of 0.656, as does full-rank spectral
initialisation with refinement. Coarse-to-sharp smoothing widens basins
and thins decoys, and recovers nothing, so below the polynomial
threshold the deficit is information the algorithm class cannot use
rather than a basin it cannot find. Solver-side candidates should wait
on the correlation instead of competing with it.

Co-Authored-By: Claude &lt;noreply@anthropic.com&gt;
</content>
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<pre>
A rank-truncation ladder from four to full rank returns chance accuracy
at the natural-data correlation of 0.656, as does full-rank spectral
initialisation with refinement. Coarse-to-sharp smoothing widens basins
and thins decoys, and recovers nothing, so below the polynomial
threshold the deficit is information the algorithm class cannot use
rather than a basin it cannot find. Solver-side candidates should wait
on the correlation instead of competing with it.

Co-Authored-By: Claude &lt;noreply@anthropic.com&gt;
</pre>
</div>
</content>
</entry>
<entry>
<title>Augmentation orbits do not substitute for multiple photographs</title>
<updated>2026-08-01T19:11:25+00:00</updated>
<author>
<name>Yuren Hao</name>
<email>blackhao0426@gmail.com</email>
</author>
<published>2026-08-01T19:11:25+00:00</published>
<link rel='alternate' type='text/html' href='https://git.blackhao.com/World-Alignment.git/commit/?id=ebc2e7f5129b81db745ad15e5b78b69a95b9837c'/>
<id>ebc2e7f5129b81db745ad15e5b78b69a95b9837c</id>
<content type='text'>
Four random resized crops per Visual Genome image, segmented
independently with their fields averaged, leave the correlation at
0.6559. Closed-world re-renders resample layout, which is nuisance by
construction, so averaging removes modality-private variation; random
crops perturb framing that self-supervised patch features already
absorb, leaving nothing to cancel.

Co-Authored-By: Claude &lt;noreply@anthropic.com&gt;
</content>
<content type='xhtml'>
<div xmlns='http://www.w3.org/1999/xhtml'>
<pre>
Four random resized crops per Visual Genome image, segmented
independently with their fields averaged, leave the correlation at
0.6559. Closed-world re-renders resample layout, which is nuisance by
construction, so averaging removes modality-private variation; random
crops perturb framing that self-supervised patch features already
absorb, leaving nothing to cancel.

Co-Authored-By: Claude &lt;noreply@anthropic.com&gt;
</pre>
</div>
</content>
</entry>
<entry>
<title>World Alignment: unpaired cross-modal correspondence by relational identifiability</title>
<updated>2026-08-01T19:10:03+00:00</updated>
<author>
<name>Yuren Hao</name>
<email>blackhao0426@gmail.com</email>
</author>
<published>2026-08-01T19:10:03+00:00</published>
<link rel='alternate' type='text/html' href='https://git.blackhao.com/World-Alignment.git/commit/?id=a62cf4d2a99b4a7985c61b2a7feb92a82a8218b7'/>
<id>a62cf4d2a99b4a7985c61b2a7feb92a82a8218b7</id>
<content type='text'>
Method: scene states are sets of part states; relation fields are built
within each modality and are invariant to how each side labels its own
features; the cross-modal bridge is a coupling searched under an energy
that is a closed-form functional of one matrix; solving is spectral
initialisation followed by exact local refinement.

Evidence: in a procedurally generated closed world, blind recovery of a
hidden image-caption correspondence reaches 95.3% at 256 scenes against
0.39% chance, and the recovered pairs transfer to 200 held-out scenes at
93.0% exact retrieval with random-pair and shuffled-image controls at or
near chance. Cross-modal value correspondence is derived from disjoint
corpora rather than declared. On Visual Genome the field correlation
reaches 0.656 against the 0.9 that polynomial recovery needs, with the
deficit attributed away from segmentation and discretisation.

Protocol: no image-text pair enters any objective, optimiser,
initialisation, or model selection; hidden pairs score orderings only.

Co-Authored-By: Claude &lt;noreply@anthropic.com&gt;
</content>
<content type='xhtml'>
<div xmlns='http://www.w3.org/1999/xhtml'>
<pre>
Method: scene states are sets of part states; relation fields are built
within each modality and are invariant to how each side labels its own
features; the cross-modal bridge is a coupling searched under an energy
that is a closed-form functional of one matrix; solving is spectral
initialisation followed by exact local refinement.

Evidence: in a procedurally generated closed world, blind recovery of a
hidden image-caption correspondence reaches 95.3% at 256 scenes against
0.39% chance, and the recovered pairs transfer to 200 held-out scenes at
93.0% exact retrieval with random-pair and shuffled-image controls at or
near chance. Cross-modal value correspondence is derived from disjoint
corpora rather than declared. On Visual Genome the field correlation
reaches 0.656 against the 0.9 that polynomial recovery needs, with the
deficit attributed away from segmentation and discretisation.

Protocol: no image-text pair enters any objective, optimiser,
initialisation, or model selection; hidden pairs score orderings only.

Co-Authored-By: Claude &lt;noreply@anthropic.com&gt;
</pre>
</div>
</content>
</entry>
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