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authorYuren Hao <blackhao0426@gmail.com>2026-08-01 14:10:03 -0500
committerYuren Hao <blackhao0426@gmail.com>2026-08-01 14:10:03 -0500
commita62cf4d2a99b4a7985c61b2a7feb92a82a8218b7 (patch)
treeee2248078db7edf3812a07f195afa3d9bd6f10c6 /artifacts/manifold_gate/ricci_flickr_test512_orbit.json
World Alignment: unpaired cross-modal correspondence by relational identifiability
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 <noreply@anthropic.com>
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+} \ No newline at end of file