Unverified50% confidenceFactExact time
Applying singular value decomposition (SVD) to the key and value weight matrices of a pretrained model can factorize them into a dimensionality-reduction projection (encoder) and a dimensionality-expansion projection (decoder), converting standard attention into a low-rank cache structure similar to multi-head latent attention (MLA).
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10/9/2026
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