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arXiv — cs.AI preprintsInternational16 October 2026

DropKV: Decoupling Residual-Output Perturbation for Near-Optimal KV-Cache Eviction

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arXiv:2610.22130v1 Announce Type: new Abstract: Key-value (KV) cache management has become a critical bottleneck for scaling Large Language Models (LLMs) to long-context scenarios due to linear memory growth. While recent eviction methods have moved beyond simple attention-score heuristics to incorporate value representations, they typically face a fundamental trade-off: the underlying optimization for minimizing output perturbation is an NP-hard combinatorial problem, leading to mathematically suboptimal heuristics or implementations that are difficult to kernelize. In this work, we propose D
— arXiv — cs.AI preprints

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