pith:MGCGHDBA
Uncovering Symmetry Transfer in Large Language Models via Layer-Peeled Optimization
Symmetries in next-token targets transfer exactly to circulant logit matrices and equiangular structures in LLM weights and embeddings.
arxiv:2605.12756 v1 · 2026-05-12 · math.OC · cs.AI · stat.ML
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Claims
we prove that when the target tokens exhibit a cyclic-shift symmetry (such as the seven days of the week or the twelve months of the year), the optimal logit matrix is exactly circulant, and the Gram matrices of both the output projections and the context embeddings form circulant geometries as well.
The constrained layer-peeled optimization program serves as a mathematically tractable surrogate for LLMs by treating the output projection matrix and last-layer context embeddings as optimization variables.
Symmetries in next-token prediction targets induce corresponding geometric symmetries such as circulant matrices and equiangular tight frames in the optimal weights and embeddings of a layer-peeled LLM surrogate model.
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| First computed | 2026-05-18T03:09:48.563146Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
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(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
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Canonical record JSON
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