Associative Algebra Layers for Efficient Transformer Projections
September 25, 2026
This approach replaces standard matrix multiplication with a sparser interaction table over weight blocks using associative algebra. The construction achieves quadratic arithmetic in the matrix dimension while remaining compatible with causal masking and KV-caching.
HOW THIS AFFECTS YOU
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builderThis could lead to significantly faster inference speeds through cheaper projection operations.
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researcherYou can explore non-standard arithmetic operators to improve transformer scaling laws.