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News/Krause Synchronization Transformers
arxiv
PublishedMay 16, 2026 at 4:00 AM
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Krause Synchronization Transformers

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arxiv.orgfull article ↗
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Publisher summary· verbatim

arXiv:2602.11534v3 Announce Type: replace-cross Abstract: Self-attention in Transformers relies on globally normalized softmax weights, causing all tokens to compete for influence at every layer. When composed across depth, this interaction pattern induces strong synchronization dynamics that favor

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  • 01meta-llama logo
    Llama-3.1-70B
    meta-llama/Llama-3.1-70B
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Discussion
Mentioned models
03
  • 01
    Llama-3.1-70B
    meta-llama/Llama-3.1-70B
  • 02
    Qwen
  • 03
    ViT
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#transformers#attention#efficiency#scalability

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Mentioned models
03
  • 01
    Llama-3.1-70B
    meta-llama/Llama-3.1-70B
  • 02
    Qwen
  • 03
    ViT
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#transformers#attention#efficiency#scalability

Related coverage

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