---
title: "Who cites DeepSpeed-FastGen: — 72 citing papers"
description: "72 papers of the Elamur Research library cite «DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and…"
canonical: "https://research.elamur.ai/free/en/papers/holmes-2024-deepspeed-fastgen-high-throughput-text/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [DeepSpeed-FastGen: High-throughput Text…](https://md.research.elamur.ai/free/en/papers/holmes-2024-deepspeed-fastgen-high-throughput-text/) / cited by

# Who cites «DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and DeepSpeed-Inference»

72 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and DeepSpeed-Inference»](https://md.research.elamur.ai/free/en/papers/holmes-2024-deepspeed-fastgen-high-throughput-text/)

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. [**HybridFlow: A Flexible and Efficient RLHF Framework arXiv:2409.19256**Guangming Sheng, Chi Zhang, Zilingfeng Ye, et al.*2024 · 624 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2024-hybridflow-flexible-efficient-rlhf-framework/)
3. **[LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism](https://md.research.elamur.ai/free/en/papers/wu-2024-loongserve-efficiently-serving-long-context/) [ACM SIGOPS Symposium on Operating Systems Principles (SOSP)](https://md.research.elamur.ai/free/en/venues/acm-sigops-symposium-on-operating-systems-principles-sosp/)**Bingyang Wu, Shengyu Liu, Yinmin Zhong, et al.*2024 · 131 citations*
4. [**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/)
5. [**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/)
6. [**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/)
7. **[Chat-Ghosting: Methods for Auto-Completion in Dialog Systems](https://md.research.elamur.ai/free/en/papers/mandal-2026-chat-ghosting-methods-auto-completion/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Anubhab Mandal, Sandeep Mishra, Bishal Santra, et al.*2026 · 1 citation*
8. **[Rectified Sparse Attention for Efficient Long-Sequence Generation](https://md.research.elamur.ai/free/en/papers/sun-2026-rectified-sparse-attention-efficient-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yutao Sun, Tianzhu Ye, Li Dong, et al.*2026 · 1 citation*

64 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/holmes-2024-deepspeed-fastgen-high-throughput-text/) — DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and DeepSpeed-Inference