---
title: "Who cites S-LoRA: Serving Thousands of — 73 citing papers"
description: "73 papers of the Elamur Research library cite «S-LoRA: Serving Thousands of Concurrent LoRA Adapters», found in their bibliographies; the…"
canonical: "https://research.elamur.ai/free/en/papers/sheng-2023-s-lora-serving-thousands-concurrent/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/sheng-2023-s-lora-serving-thousands-concurrent/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [S-LoRA: Serving Thousands of Concurrent LoRA…](https://md.research.elamur.ai/free/en/papers/sheng-2023-s-lora-serving-thousands-concurrent/) / cited by

# Who cites «S-LoRA: Serving Thousands of Concurrent LoRA Adapters»

73 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «S-LoRA: Serving Thousands of Concurrent LoRA Adapters»](https://md.research.elamur.ai/free/en/papers/sheng-2023-s-lora-serving-thousands-concurrent/)

1. **[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*
2. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
3. **[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*
4. [**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/)
5. **[LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin](https://md.research.elamur.ai/free/en/papers/dou-2024-loramoe-alleviating-world-knowledge-forgetting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shihan Dou, Enyu Zhou, Yan Liu, et al.*2024 · 93 citations*
6. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战) Acta Automatica Sinica (自动化学报)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/sheng-2023-s-lora-serving-thousands-concurrent/) — S-LoRA: Serving Thousands of Concurrent LoRA Adapters