Research

MaRK: Markov-adapted Recurrent Kernels for Dynamic Operator Conditioning in State Space Models

Single source1 source8 Oct 2026

arXiv:2610.09092v2 Announce Type: replace-cross Abstract: State Space Models (SSMs) offer an efficient alternative to Transformers for sequence modeling, yet conditioning pre-trained SSMs for iterative generation typically operates outside the recurrent operat

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arxiv.orghttps://arxiv.org/abs/2610.09092

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