Unverified50% confidenceFactExact time
KDA (Kernelized Delta Attention) kernels the Delta rule, attempting to find a smoother interpolation between the recursive state and attention.
1
Sources
50%
Confidence
Long-term
Relevance
10/16/2026
First Seen
Sources
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Related Claims
UnverifiedKDA is a linear attention mechanism variant that uses a fixed-size recurrent state and does not retain KV cache.71% similarUnverifiedDeltaNet is a variant of linear attention that replaces softmax attention with a delta update rule, reducing sequence processing complexity from O(n²) to O(n).66% similarUnverifiedMamba-2, Gated DeltaNet and KDA are three new state update mechanisms used to replace some attention layers, achieving efficient state memory through a recursive structure with linear complexity.64% similarUnverifiedThe KV Cache in the attention mechanism is the primary contributor to GPU memory usage during inference.59% similarUnverifiedKL divergence plays the role of a regularization term in variational autoencoders (VAEs), constraining the distributional shape of the latent space58% similar
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