Towards million-token context windows: a topology-preserving framework for adaptive transformer sparsification

Transformer self-attention and billion-node network analyses share a key limitation: all-to-all evaluation creates an O(N^2) computational cost. Existing methods address this by either distributing the workload across hardware or substituting recurrent operators. This trades associative recall f…

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