---
title: "Who cites Tutel: Adaptive Mixture-of-Experts at Scale"
description: "136 papers of the Elamur Research library cite «Tutel: Adaptive Mixture-of-Experts at Scale», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/hwang-2022-tutel-adaptive-mixture-experts-scale/cited-by/"
---
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# Who cites «Tutel: Adaptive Mixture-of-Experts at Scale»

136 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 «Tutel: Adaptive Mixture-of-Experts at Scale»](https://md.research.elamur.ai/free/en/papers/hwang-2022-tutel-adaptive-mixture-experts-scale/)

1. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
2. [**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/)
3. [**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/)
4. **[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*
5. [**SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling arXiv:2312.15166**Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-solar-10-7b-scaling-large/)
6. **[Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning](https://md.research.elamur.ai/free/en/papers/an-2024-fire-flyer-ai-hpc/) [2012 International Conference for High Performance Computing, Networking, Storage and Analysis](https://md.research.elamur.ai/free/en/venues/2012-international-conference-for-high-performance-computing-networking-storage/)**Wei An, Xiao Bi, Guanting Chen, et al.*2024 · 34 citations*
7. **[Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models](https://md.research.elamur.ai/free/en/papers/qiu-2025-demons-detail-implementing-load-balancing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihan Qiu, Zeyu Huang, Bo Zheng, et al.*2025 · 21 citations*
8. **[Survey on Key Technologies for Large Language Model Pre-training Systems (大语言模型预训练系统关键技术综述)](https://md.research.elamur.ai/free/en/papers/gao-2025-key-technologies-large/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yanjie Gao (高彦杰), Yueguo Chen (陈跃国)*2025*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/hwang-2022-tutel-adaptive-mixture-experts-scale/) — Tutel: Adaptive Mixture-of-Experts at Scale