--- title: "Who cites Zhengxin Zhang — 113 papers of our library" description: "113 papers of the Elamur Research library cite the works of Zhengxin Zhang, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/zhengxin-zhang/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhengxin-zhang/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Zhengxin Zhang](https://md.research.elamur.ai/free/en/authors/zhengxin-zhang/) / cited by # Who cites Zhengxin Zhang 113 citations of their works from 113 papers of our library (of the 149,439 whose bibliographies we read) · 23 with a page here, the most cited first · [← Zhengxin Zhang](https://md.research.elamur.ai/free/en/authors/zhengxin-zhang/) 1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations* 2. **[SnapKV: LLM Knows What You are Looking for Before Generation](https://md.research.elamur.ai/free/en/papers/li-2024-snapkv-llm-knows-looking-before/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuhong Li, Yingbing Huang, Bowen Yang, et al.*2024 · 355 citations* 3. [**Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads arXiv:2401.10774**Tianle Cai, Yuhong Li, Zhengyang Geng, et al.*2024 · 278 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-medusa-simple-llm-inference-acceleration/) 4. **[PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU](https://md.research.elamur.ai/free/en/papers/song-2023-powerinfer-fast-large-language-model/) [ACM SIGOPS Symposium on Operating Systems Principles (SOSP)](https://md.research.elamur.ai/free/en/venues/acm-sigops-symposium-on-operating-systems-principles-sosp/)**Yixin Song, Zeyu Mi, Haotong Xie, et al.*2023 · 272 citations* 5. [**EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty arXiv:2401.15077**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 208 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-speculative-sampling-requires-rethinking/) 6. [**FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving MLSys 2025**Zihao Ye, Lequn Chen, Ruihang Lai, et al.*2025 · 177 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-flashinfer-efficient-customizable-attention-engine/) 7. **[EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-2-faster-inference-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 133 citations* 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. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/) 10. **[Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation](https://md.research.elamur.ai/free/en/papers/xia-2023-speculative-decoding-exploiting-speculative-execution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Heming Xia, Tao Ge, Peiyi Wang, et al.*2023 · 103 citations* 11. [**Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security arXiv:2401.05459**Yuanchun Li, Hao Wen, Weijun Wang, et al.*2024 · 100 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-personal-llm-agents-insights-survey/) 12. [**LLM Inference Unveiled: Survey and Roofline Model Insights arXiv 2024**Zhihang Yuan, Yuzhang Shang, Yang Zhou, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2024-llm-inference-unveiled-survey-roofline/) 13. [**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/) 14. [**Punica: Multi-Tenant LoRA Serving MLSys 2024**Lequn Chen, Zihao Ye, Yongji Wu, et al.*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-punica-multi-tenant-lora-serving/) 15. **[AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning](https://md.research.elamur.ai/free/en/papers/fu-2025-areal-large-scale-asynchronous-reinforcement/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wei Fu, Jiaxuan Gao, Xujie Shen, et al.*2025 · 80 citations* 16. [**S-LoRA: Serving Thousands of Concurrent LoRA Adapters MLSys 2024**Ying Sheng, Shiyi Cao, Dacheng Li, et al.*2023 · 80 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2023-s-lora-serving-thousands-concurrent/) 17. [**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/) 18. [**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/) 19. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/) 20. **[Speculative Decoding Speed-of-Light: Optimal Lower Bounds via Branching Random Walks](https://md.research.elamur.ai/free/en/papers/pankratov-2026-speculative-decoding-speed-light-optimal/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sergey Pankratov, Dan Alistarh*2026 · 1 citation* 21. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.*2026* 22. **[MARS: Unleashing the Power of Speculative Decoding via Margin-Aware Verification](https://md.research.elamur.ai/free/en/papers/song-2026-mars-unleashing-power-speculative-decoding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingwei Song, Xinyu Wang, Hanbin Wang, et al.*2026* 23. **[SPIDE: Serial and Parallel Intertwined Speculative Decoding](https://md.research.elamur.ai/free/en/papers/xu-2026-spide-serial-parallel-intertwined-speculative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenru Xu, Peixuan Xu, Ziqi Yang, et al.*2026* 90 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/zhengxin-zhang/) — Zhengxin Zhang