🔗 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»

1. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
2. A Survey on Efficient Inference for Large Language ModelsarXiv:2404.14294Zixuan Zhou, Xuefei Ning, Ke Hong, et al.2024 · 113 citations
3. Efficient Large Language Models: A SurveyarXiv:2312.03863Zhongwei Wan, Xin Wang, Che Liu, et al.2023 · 110 citations
4. Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to SystemsACM Computing SurveysXupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.2023 · 110 citations
5. SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-ScalingarXiv:2312.15166Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.2023 · 77 citations
6. Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning2012 International Conference for High Performance Computing, Networking, Storage and AnalysisWei 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 ModelsAnnual Meeting of the Association for Computational Linguistics (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)Journal of SoftwareYanjie Gao (高彦杰), Yueguo Chen (陈跃国)2025

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

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