---
title: "Who cites Esha Choukse — 423 papers of our library"
description: "423 papers of the Elamur Research library cite the works of Esha Choukse, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/esha-choukse/cited-by/"
---
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# Who cites Esha Choukse

483 citations of their works from 423 papers of our library (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← Esha Choukse](https://md.research.elamur.ai/free/en/authors/esha-choukse/)

1. [**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/)
2. [**Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve OSDI 2024**Amey Agrawal, Nitin Kedia, Ashish Panwar, et al.*2024 · 369 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2024-taming-throughput-latency-tradeoff-llm/)
3. **[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*
4. [**Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving FAST 2025**Ruoyu Qin, Zheming Li, Weiran He, et al.*2024 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-mooncake-kvcache-centric-disaggregated-architecture/)
5. [**Atom: Low-bit Quantization for Efficient and Accurate LLM Serving MLSys 2024**Yilong Zhao, Chien-Yu Lin, Kan Zhu, et al.*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-atom-low-bit-quantization-efficient/)
6. **[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*
7. [**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/)
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. **[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*
10. [**Cost-Efficient Large Language Model Serving for Multi-turn Conversations with CachedAttention USENIX ATC 2024**Bin Gao, Zhuomin He, Puru Sharma, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-cost-efficient-large-language-model/)
11. [**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/)
12. [**Vidur: A Large-Scale Simulation Framework For LLM Inference arXiv:2405.05465**Amey Agrawal, Nitin Kedia, Jayashree Mohan, et al.*2024 · 90 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2024-vidur-large-scale-simulation-framework/)
13. **[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*
14. [**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/)
15. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
16. [**A Survey of Small Language Models arXiv:2410.20011**Chien Van Nguyen, Xuan Shen, Ryan Aponte, et al.*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2024-survey-small-language-models/)
17. [**Step-3 is Large yet Affordable: Model-system Co-design for Cost-effective Decoding arXiv:2507.19427**StepFun, Bin Wang, Bojun Wang, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/stepfun-2025-step-3-large-yet/)
18. **[PDTrim: Targeted Pruning for Prefill-Decode Disaggregation in Inference](https://md.research.elamur.ai/free/en/papers/zhang-2026-pdtrim-targeted-pruning-prefill-decode/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Zhang, Lyu Mengsi, Zhuo Chen, et al.*2026 · 6 citations*

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

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