---
title: "Who cites Zhenhua Han — 205 papers of our library"
description: "205 papers of the Elamur Research library cite the works of Zhenhua Han, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/zhenhua-han/cited-by/"
---
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# Who cites Zhenhua Han

230 citations of their works from 205 papers of our library (of the 149,439 whose bibliographies we read) · 31 with a page here, the most cited first · [← Zhenhua Han](https://md.research.elamur.ai/free/en/authors/zhenhua-han/)

1. **[MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention](https://md.research.elamur.ai/free/en/papers/jiang-2024-minference-1-0-accelerating-pre/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.*2024 · 202 citations*
2. [**PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling arXiv:2406.02069**Zefan Cai, Yichi Zhang, Bofei Gao, et al.*2024 · 155 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-pyramidkv-dynamic-kv-cache-compression/)
3. [**Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention arXiv:2502.11089**Jingyang Yuan, Huazuo Gao, Damai Dai, et al.*2025 · 142 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2025-native-sparse-attention-hardware/)
4. [**DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads arXiv:2410.10819**Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2024-duoattention-efficient-long-context-llm/)
5. [**Qwen2.5-1M Technical Report arXiv:2501.15383**An Yang, Bowen Yu, Chengyuan Li, et al.*2025 · 102 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-qwen2-5-1m-technical/)
6. **[MoBA: Mixture of Block Attention for Long-Context LLMs](https://md.research.elamur.ai/free/en/papers/lu-2025-moba-mixture-block-attention/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Enzhe Lu, Zhejun Jiang, Jingyuan Liu, et al.*2025 · 80 citations*
7. **[SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration](https://md.research.elamur.ai/free/en/papers/zhang-2024-sageattention-accurate-8-bit-attention/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Jintao Zhang, Jia Wei, Haofeng Huang, et al.*2024 · 74 citations*
8. [**MagicPIG: LSH Sampling for Efficient LLM Generation arXiv:2410.16179**Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/)
9. **[RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval](https://md.research.elamur.ai/free/en/papers/liu-2024-retrievalattention-accelerating-long-context-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Di Liu, Meng Chen, Baotong Lu, et al.*2024 · 66 citations*
10. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
11. [**XAttention: Block Sparse Attention with Antidiagonal Scoring arXiv:2503.16428**Ruyi Xu, Guangxuan Xiao, Haofeng Huang, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-xattention-block-sparse-attention-antidiagonal/)
12. [**Long Context Compression with Activation Beacon arXiv:2401.03462**Peitian Zhang, Zheng Liu, Shitao Xiao, et al.*2024 · 47 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-long-context-compression-activation-beacon/)
13. **[LongReward: Improving Long-context Large Language Models with AI Feedback](https://md.research.elamur.ai/free/en/papers/zhang-2025-longreward-improving-long-context-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiajie Zhang, Zhongni Hou, Xin Lv, et al.*2025 · 21 citations*
14. **[Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction](https://md.research.elamur.ai/free/en/papers/shi-2026-discovering-gems-early-layers-accelerating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenmei Shi, Yifei Ming, Xuan-Phi Nguyen, et al.*2026 · 13 citations*
15. **[The Sparse Frontier: Sparse Attention Trade-offs in Transformer LLMs](https://md.research.elamur.ai/free/en/papers/nawrot-2026-sparse-frontier-sparse-attention-trade/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Piotr Nawrot, Jianing Li, Renjie Huang, et al.*2026 · 10 citations*
16. [**MiniMax Sparse Attention arXiv:2606.13392**Xunhao Lai, Weiqi Xu, Yufeng Yang, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/lai-2026-minimax-sparse-attention/)
17. **[Adaptive Layer Selection for Layer-Wise Token Pruning in LLM Inference](https://md.research.elamur.ai/free/en/papers/taniguchi-2026-adaptive-layer-selection-layer-wise/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rei Taniguchi, Yuyang Dong, Makoto Onizuka, et al.*2026 · 1 citation*
18. **[DELTA: Dynamic Layer-Aware Token Attention for Efficient Long-Context Reasoning](https://md.research.elamur.ai/free/en/papers/zarch-2026-delta-dynamic-layer-aware-token/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hossein Entezari Zarch, Lei Gao, Chaoyi Jiang, et al.*2026 · 1 citation*
19. **[KG-MuLQA: A Framework for KG-based Multi-Level QA Extraction and Long-Context LLM Evaluation](https://md.research.elamur.ai/free/en/papers/tatarinov-2026-kg-mulqa-framework-kg-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nikita Tatarinov, Vidhyakshaya Kannan, Haricharana Srinivasa, et al.*2026 · 1 citation*
20. **[LiveLongBench: Tackling Long-Context Understanding for Spoken Texts from Live Streams](https://md.research.elamur.ai/free/en/papers/wu-2026-livelongbench-tackling-long-context-understanding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yongxuan Wu, Runyu Chen, Peiyu Liu, et al.*2026 · 1 citation*
21. **[Exploring Fine-Tuning for In-Context Retrieval and Efficient KV-Caching in Long-Context Language Models](https://md.research.elamur.ai/free/en/papers/molfese-2026-exploring-fine-tuning-context-retrieval/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Francesco Maria Molfese, Momchil Hardalov, Rexhina Blloshmi, et al.*2026*
22. **[GRASPrune: Global Gating for Budgeted Structured Pruning of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-grasprune-global-gating-budgeted-structured/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyang Wang, Jiangfeng Xiao, Chuan Xiao, et al.*2026*
23. **[HeteroCache: A Dynamic Retrieval Approach to Heterogeneous KV Cache Compression for Long-Context LLM Inference](https://md.research.elamur.ai/free/en/papers/shi-2026-heterocache-dynamic-retrieval-approach-heterogeneous/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyuan Shi, Qibo Qiu, Xuefeng, et al.*2026*
24. **[Latent-Condensed Transformer for Efficient Long Context Modeling](https://md.research.elamur.ai/free/en/papers/you-2026-latent-condensed-transformer-efficient-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zeng You, Yaofo Chen, Qiuwu Chen, et al.*2026*
25. **[LEDGER: Scaling Agentic Document Editing with Dependency-aware Graph Retrieval](https://md.research.elamur.ai/free/en/papers/wang-2026-ledger-scaling-agentic-document-editing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hang Wang, Utkarsh Garg, Reza Davari, et al.*2026*
26. **[Question Tells You Where the Answer Is: Intention-aware Long-Context KV Cache Compression](https://md.research.elamur.ai/free/en/papers/zhao-2026-question-tells-you-where-answer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liang Zhao, Xiaocheng Feng, Weihong Zhong, et al.*2026*
27. **[QueueEDIT: Structural Self-Correction for Sequential Model Editing in LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-queueedit-structural-self-correction-sequential/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taolin Zhang, Haidong Kang, Dongyang Li, et al.*2026*
28. **[RoBSA: RoPE-based Blockwise Sparse Multi-head Latent Attention](https://md.research.elamur.ai/free/en/papers/shi-2026-robsa-rope-based-blockwise-sparse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Shi, Kairong Luo, Zhen Zheng, et al.*2026*
29. **[RRAtention: Dynamic Block Sparse Attention via Per-Head Round-Robin Shifts for Long-Context Inference](https://md.research.elamur.ai/free/en/papers/liu-2026-rratention-dynamic-block-sparse-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siran Liu, Guoxia Wang, Sa Wang, et al.*2026*
30. **[S2O: Early Stopping for Sparse Attention via Online Permutation](https://md.research.elamur.ai/free/en/papers/zhang-2026-s2o-early-stopping-sparse-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Zhang, Songwei Liu, Chenqian Yan, et al.*2026*
31. **[VecInfer: Efficient LLM Inference with Low-Bit KV Cache via Outlier-Suppressed Vector Quantization](https://md.research.elamur.ai/free/en/papers/yao-2026-vecinfer-efficient-llm-inference-low/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dingyu Yao, Chenxu Yang, Zhengyang Tong, et al.*2026*

174 more citing papers of our library have no page here yet.

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