---
title: "Who cites AlpaServe: Statistical — 151 citing papers"
description: "151 papers of the Elamur Research library cite «AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving», found…"
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---
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# Who cites «AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving»

151 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · [← back to «AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving»](https://md.research.elamur.ai/free/en/papers/li-2023-alpaserve-statistical-multiplexing-model-parallelism/)

1. [**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/)
2. [**DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving OSDI 2024**Yinmin Zhong, Shengyu Liu, Junda Chen, et al.*2024 · 409 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-distserve-disaggregating-prefill-decoding-goodput/)
3. [**Splitwise: Efficient generative LLM inference using phase splitting ISCA 2024**Pratyush Patel, Esha Choukse, Chaojie Zhang, et al.*2023 · 379 citations*](https://md.research.elamur.ai/free/en/papers/patel-2023-splitwise-efficient-generative-llm-inference/)
4. **[DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency](https://md.research.elamur.ai/free/en/papers/stojkovic-2024-dynamollm-designing-llm-inference-clusters/) [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/)**Jovan Stojkovic, Chaojie Zhang, Inigo Goiri, et al.*2024 · 218 citations*
5. **[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*
6. [**Fast Distributed Inference Serving for Large Language Models arXiv 2023**Bingyang Wu, Yinmin Zhong, Zili Zhang, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-fast-distributed-inference-serving-large/)
7. [**Llumnix: Dynamic Scheduling for Large Language Model Serving OSDI 2024**Biao Sun, Ziming Huang, Hanyu Zhao, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-llumnix-dynamic-scheduling-large-language/)
8. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
9. [**ServerlessLLM: Low-Latency Serverless Inference for Large Language Models arXiv:2401.14351**Yao Fu, Leyang Xue, Yeqi Huang, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-serverlessllm-low-latency-serverless-inference/)
10. [**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/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/li-2023-alpaserve-statistical-multiplexing-model-parallelism/) — AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving