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Role-Decoupled Attention Residuals: Separating Matching and Content Retrieval Ac
BACKGROUND
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5 Aug
Role-Decoupled Attention Residuals: Separating Matching and Content Retrieval Across Depth
REPORT · WHAT · ArXiv CS.AI
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26 Mar
Scaling Attention via Feature Sparsity
arXiv:2603.22300v1 Announce Type: cross Abstract: Scaling Transformers to ultra-long contexts is bottlenecked by the $O(n^2 d)$ cost of self-attention. Existing methods reduce
REPORT · WHERE · ArXiv CS.AIOPEN STORY
7 Apr
Attention Residuals: How Kimi Is Rethinking Transformer Depth
<p>Every transformer you've ever used stacks layers with a dead-simple formula: take the input, add the layer's output, move on. <code>x + layer(x)</code>. Fixed weight of 1. No
REPORT · HOW · Dev.toOPEN STORY
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