Papers by Minwei Zhang

1 papers
ClusterAttn: KV Cache Compression under Intrinsic Attention Clustering (2025.acl-long)

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Challenge: Existing methods for sparse attention apply the same pattern across different attention heads and inputs, but fail to capture the intrinsic attention clustering in large language models.
Approach: They propose a training-free sparse attention method that provides an efficient prompt cache compression scheme under intrinsic attention clustering for efficient LLM inference.
Outcome: The proposed method reduces memory usage by 10%–65% and increases throughput by 2.6–4.8 times with no accuracy loss.

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