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RBF-Attention – Trading dot-products for Euclidean distance

RBF-Attention – Trading dot-products for Euclidean distance

by 4rtemi5·Apr 7, 2026·1 point·1 comment

AI Analysis

●●●BangerBig BrainWizardry

Replaces dot-product attention with Euclidean distance to stop vector magnitude bullying.

Strengths
  • Identifies specific "magnitude bullying" flaw in standard scaled dot-product attention math.
  • Includes custom Triton kernel for memory-efficient implementation on existing hardware.
  • Trained a causal LM from scratch to validate empirical results against standard attention.
Weaknesses
  • Experimental nature means no production libraries or pre-trained models available yet.
  • Hardware acceleration for dot-products is ubiquitous, distance might be slower on GPUs.
Category
Target Audience

ML researchers, LLM engineers

Similar To

FlashAttention · xFormers · Standard Transformers

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