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RBS-Attention: Radius-Bounded Sparse Prefill for Long-Context Large Language Models
Long-context large language model inference is increasingly limited by prefill, where dense self-attention processes the entire prompt before generation begins. Sparse block selection can reduce this cost, but a block centroid may hide a highly relevant token among many irrelevant ones. We call this
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