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SMat-Attention: Structured Long-Context Sequence Modeling

Anand, Emile et al.
arXiv (All) · Papers
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Long-context sequence models face a fundamental tradeoff: softmax attention uses flexible token-level interactions at quadratic cost, whereas linear attention obtains linear-time training and constant-time decoding by compressing history into a fixed-size state. In this work, we ask whether we can c
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