Author

Hao Gu

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Preprint Jul 2026

Hierarchical Sparse Attention Done Right: Toward Infinite Context Modeling

Hierarchical Landmark Sparse Attention is proposed, a chunk-wise sparse attention mechanism that learns chunk selection end-to-end under the language-modeling (LM) loss, enabling long-context LLMs that are both more efficient and more effective on general long-context tasks than their full-attention counterparts.

Xiang Hu, Xinyu Wei, Hao Gu et al. · 3 citations

Preprint Aug 2026

Fewer Tokens, Smaller Cache: Reward-Coordinated Efficient Reasoning

ReCo (Reward-Coordinated Compression), a step-wise framework in which a lightweight process-reward estimator scores each completed step and drives three components: reward-adaptive KV-cache compression that shrinks the retained cache harder at high-reward steps and less at low-reward ones, and a confidence-based early stopping that triggers when the reasoning is reliable.

Qiyuan Zhu, Dezhi Li, Pengyu Cheng et al. · 0 citations