--- title: "Who cites Hanrui Wang — 181 papers of our library" description: "181 papers of the Elamur Research library cite the works of Hanrui Wang, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/hanrui-wang/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/hanrui-wang/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Hanrui Wang](https://md.research.elamur.ai/free/en/authors/hanrui-wang/) / cited by # Who cites Hanrui Wang 192 citations of their works from 181 papers of our library (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← Hanrui Wang](https://md.research.elamur.ai/free/en/authors/hanrui-wang/) 1. **[Efficient Transformers: A Survey](https://md.research.elamur.ai/free/en/papers/tay-2020-efficient-transformers-survey/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Yi Tay, Mostafa Dehghani, Dara Bahri, et al.*2020 · 1,539 citations* 2. **[SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning](https://md.research.elamur.ai/free/en/papers/wang-2020-spatten-efficient-sparse-attention-architecture/) [Proceedings - International Symposium on High-Performance Computer Architecture/Proceedings](https://md.research.elamur.ai/free/en/venues/proceedings-international-symposium-on-high-performance-computer-architecture/)**Hanrui Wang, Zhekai Zhang, Song Han*2020 · 534 citations* 3. **[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* 4. **[LLM in a flash: Efficient Large Language Model Inference with Limited Memory](https://md.research.elamur.ai/free/en/papers/alizadeh-2024-llm-flash-efficient-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Keivan Alizadeh, Seyed Iman Mirzadeh, Dmitry Belenko, et al.*2024 · 193 citations* 5. **[Efficient Methods for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.*2023 · 145 citations* 6. [**H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models arXiv:2306.14048**Zhenyu Zhang, Ying Sheng, Tianyi Zhou, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-h-2-o-heavy-hitter/) 7. [**QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving MLSys 2025**Yujun Lin, Haotian Tang, Shang Yang, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-qserve-w4a8kv4-quantization-system-co/) 8. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/) 9. [**REST: Retrieval-Based Speculative Decoding arXiv:2311.08252**Zhenyu He; Zexuan Zhong; Tianle Cai; Jason D. Lee;, Di He*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-rest-retrieval-based-speculative-decoding/) 10. [**Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation arXiv:2307.15337**Xuefei Ning, Zinan Lin, Zixuan Zhou, et al.*2023 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ning-2023-skeleton-thought-prompting-llms-efficient/) 11. **[Softpick: No Attention Sink, No Massive Activations with Rectified Softmax](https://md.research.elamur.ai/free/en/papers/zuhri-2026-softpick-no-attention-sink-no/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zayd Muhammad Kawakibi Zuhri, Erland Hilman Fuadi, Alham Fikri Aji*2026 · 6 citations* 12. **[Cross-layer Attention Sharing for Pre-trained Large Language Models](https://md.research.elamur.ai/free/en/papers/mu-2026-cross-layer-attention-sharing-pre/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yongyu Mu, Yuzhang Wu, Yuchun Fan, et al.*2026 · 2 citations* 13. **[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* 168 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/hanrui-wang/) — Hanrui Wang