Unverified50% confidenceFactExact time
In the Transformer architecture, the KV Cache stores the Key and Value vectors corresponding to each token in the attention mechanism.
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50%
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Long-term
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9/18/2026
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Related Claims
UnverifiedTransformer 架构中自注意力层会为每个 Token 生成对应的 Key 和 Value 向量并缓存在 GPU 显存中，即 KV Cache 机制，上下文越长占用显存越大，推理成本呈近线性增长80% similarVerifiedKV Cache is the persistent storage of intermediate states in the Transformer attention mechanism, recording the key and value vectors for each attention head's processed tokens across all layers, thereby skipping redundant forward propagation computations.80% similarUnverifiedIn the Transformer architecture, generating each new token requires attention computation over all previous tokens, and KV Cache avoids redundant computation by caching previously computed key-value pairs.77% similarUnverifiedTransformer 的自注意力机制通过 Query、Key、Value 三个矩阵对输入序列并行计算，使每个 token 能同时关注序列中所有其他 token75% similarVerifiedIn the Transformer self-attention mechanism, each token must compute attention weights with all other tokens within the window, giving a computational complexity of O(n²).74% similar
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