RIS-Kernel claims O(N log N) sparse attention via ensembled random masks for long-context CPU inference, but the complexity claim conflicts with the paper's fixed-density mask design and the accuracy evidence is statistically weak.
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RIS-Kernel: A Model-Agnostic Architecture for Long-Context LLM Inference via Sparse Attention
RIS-Kernel claims O(N log N) sparse attention via ensembled random masks for long-context CPU inference, but the complexity claim conflicts with the paper's fixed-density mask design and the accuracy evidence is statistically weak.