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Eviction as Estimation: A Fixed-Lag Smoothing View of Test-Time Memory, and When Measuring Beats Accumulating
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers propose RMM, a fixed-lag smoothing approach to decide which cached tokens to keep in language models with bounded memory.
- 为何重要
- Matters for engineers optimizing inference on resource-constrained systems where KV cache management directly impacts throughput and latency.
- 注意
- Method matches existing approaches on standard benchmarks; gains appear only when token reuse is sharp and endogenous, not typical in real workloads.
收听本摘要
- llm
- language model
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