arXiv — Machine Learning · · 3 min read

Semidirect Fourier Delta Attention: Phase-Controlled Delta Memory with Constructive Chunk-WY Kernels

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Computer Science > Machine Learning

arXiv:2607.11897 (cs)
[Submitted on 12 Jun 2026]

Title:Semidirect Fourier Delta Attention: Phase-Controlled Delta Memory with Constructive Chunk-WY Kernels

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Abstract:Linear attention replaces softmax attention's growing KV cache with a fixed recurrent state, but this compression limits exact state tracking and long-context memory. We introduce \emph{Semidirect Fourier Delta Attention} (SFDA), a phase-controlled generalization of Kimi Delta Attention that replaces real diagonal decay with block-rotational Fourier control: \[ S_t=(I-\beta_t k_tk_t^*)\Lambda_tS_{t-1}+\beta_tk_tv_t^*, \qquad \Lambda_t=\diag(\alpha_t\odot e^{i\theta_t}). \] Our main result is a constructive chunk-WY factorization for products \(A_t=\Lambda_t-u_tr_t^*\), giving \[ A_t\cdots A_1=\Gamma_t-Y_tM_tW_t^* \] with rank growth bounded inside fixed chunks. This yields an exact affine chunk transfer, formal stability and complexity bounds, and a compact characterization of phase-plus-low-rank memory. We verify the algebra numerically and show in toy state-tracking experiments that SFDA learns cyclic memory where the phase-disabled KDA baseline remains near chance. Fused kernels and large-scale language-model comparisons are left to future work.
Subjects: Machine Learning (cs.LG)
Cite as: arXiv:2607.11897 [cs.LG]
  (or arXiv:2607.11897v1 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2607.11897
arXiv-issued DOI via DataCite

Submission history

From: Tiantian Zhang [view email]
[v1] Fri, 12 Jun 2026 17:31:03 UTC (151 KB)
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