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Personalized memory gating unlocks more relevant long-term recall by learning from individual user interaction patterns, outperforming generic policies.
Complex scoring algorithms for KV cache compression are largely unnecessary: protecting the initial prompt and dropping reasoning tokens completely at random matches state-of-the-art accuracy with up to 43% higher serving throughput.