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We formalize this view by defining order-induced pseudo-joints and a local denoising circulation: the log-ratio between the two pseudo-joints obtained by swapping a pair of unresolved positions. This circulation is zero under compatible conditionals, and global order gaps decompose into sums of local circulations along adjacent swaps. We further separate incompatibility-driven path dependence from conditional-dependence error in parallel updates and from order-specific estimation error. The resulting framework provides inference-only diagnostics for testing when DLM decoding is genuinely order-free.
| Subjects: | Machine Learning (cs.LG) |
| Cite as: | arXiv:2605.09303 [cs.LG] |
| (or arXiv:2605.09303v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2605.09303 arXiv-issued DOI via DataCite (pending registration) |
From: Jeonseong Kim [view email]
[v1]
Sun, 10 May 2026 04:00:52 UTC (17 KB)
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