Unverified50% confidenceFactExact time
Methods for compressing the KV Cache include quantization, low-rank approximation, and evicting old tokens by importance; their direct effect is to increase the number of tokens (capacity) that a unit of GPU memory can hold, rather than to save compute or transfer.
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50%
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Long-term
Relevance
10/19/2026
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UnverifiedMLA 将所有头的 Key 和 Value 联合压缩为低维潜在向量缓存，本质上是对 KV Cache 做低秩分解79% similarUnverifiedWhen implementing a KV cache, one should compare the cached and uncached versions token by token on greedy output over long sequences (e.g., more than 200 tokens) rather than only performing single-step validation, in order to effectively verify cache correctness.79% similarUnverified上下文越长，模型需要缓存的 KV Cache 越大，KV Cache 使模型生成新 Token 时无需重新计算所有历史 Token 的注意力权重78% similarVerifiedKV Cache avoids redundant computation by caching already-computed Key and Value matrices, and advanced techniques such as PagedAttention further optimize cache memory management efficiency.77% similarUnverifiedKV Cache（键值缓存）用于避免自回归生成时对历史 token 的重复计算，但长上下文场景下预填充阶段需占用大量 HBM 显存带宽，拉长首 token 延迟（TTFT）76% similar
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