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arXiv cs.AI
  • Score 75
  • Official

RBS-Attention: Radius-Bounded Sparse Prefill for Long-Context Large Language Models

arXiv:2609.20971v1 Announce Type: new Abstract: 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 failure mode mean dilution and propose RBS-Attentio

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  • ResearcherEAP-identified components cluster in specific layers but do not align with the layers showing the largest fine-tuning representational change, so activation-dri

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RelevanceHow tightly this is about AI.
72
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45
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68
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92
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30
RBS-Attention: Radius-Bounded Sparse Prefill for Long-Context Large Language Models · AboutAI