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CwA can boost nearest neighbor search throughput by up to 4.7 times compared to existing methods when database and query distributions vary.
Scaling linear attention models with Sparse Delta Memory leads to significant improvements in long-context recall and reasoning without the computational burden of larger state sizes.
