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News/Attention Once Is All You Need: Efficient Streaming Inference with Stateful Transformers
arxiv
PublishedMay 14, 2026 at 4:00 AM
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Attention Once Is All You Need: Efficient Streaming Inference with Stateful Transformers

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Publisher summary· verbatim

arXiv:2605.13784v1 Announce Type: new Abstract: Conventional transformer inference engines are request-driven, paying an O(n) prefill cost on every query. In streaming workloads, where data arrives continuously and queries probe an ever-growing context, this cost is prohibitive. We introduce a data-

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Discussion
Mentioned models
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  • 01
    vLLM
  • 02
    SGLang
  • 03
    TensorRT-LLM
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arxiv
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#streaming#inference#optimization#machine learning

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Mentioned models
03
  • 01
    vLLM
  • 02
    SGLang
  • 03
    TensorRT-LLM
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#streaming#inference#optimization#machine learning

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