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Evidence record 16718 · automatically gathered

AdaK: adaptive KV cache budget estimation framework for analyzing long-context large language model inference

IntroductionThe deployment of LLMs on resource-constrained hardware is hindered by the memory-intensive KV Cache mechanism.MethodsWe propose AdaK, an adaptive KV cache budget estimation framework with three strategies: entropy-based thresholding, task-aware lookup table, and a lightweight policy network.ResultsAdaK reveals estimated KV cache reductions of up to 17.9% relative to fixed-k = 2048 baselines across 16 settings on Qwen3-4B, Qwen3-8B, and Mistral-7B.DiscussionAdaK's decoupled design en

Record details

Published: 5 August 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Regulation
Retrieved: 6 August 2026

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How to cite this record

ethics.ai (5 August 2026), “AdaK: adaptive KV cache budget estimation framework for analyzing long-context large language model inference,” evidence record 16718, https://ethics.ai/record/16718 (originally published by Frontiers in Artificial Intelligence).

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