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

Krause Synchronization Transformers

Source
arxiv.orgfull article ↗
Read on arxiv→
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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    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

No replies yet. Be first.

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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