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Minshen Zhang

Core-contributor-marked author of HiLS-Attention with paper-time affiliation UC San Diego. Homepage identifies Minshen Zhang as a UCSD master student in Hao AI Lab with prior ShanghaiTech training under Kewei Tu and Ant Group work integrating hierarchical sparse attention into SGLang.

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归档 Jul 09, 2026

Hierarchical Sparse Attention Done Right: Toward Infinite Context Modeling

HiLS Attention 用 landmark 压缩键、熵偏置与分层 softmax 训练 chunk 选择器，使 8K 训练的 345M 模型在 4M RULER 单针检索仍得 96 分，并在 512K 单 H800、batch size 1 的同 Triton 基线上将 prefill 与 decode 分别加速 13.5 倍和 15.7 倍。

待审阅 2607.02980-hils-attention-infinite-context Sparse Attention Long Context