🔗 Who cites «PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU»

139 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · ← back to «PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU»

1. HybridFlow: A Flexible and Efficient RLHF FrameworkarXiv:2409.19256Guangming Sheng, Chi Zhang, Zilingfeng Ye, et al.2024 · 624 citations
2. DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model ServingOSDI 2024Yinmin Zhong, Shengyu Liu, Junda Chen, et al.2024 · 409 citations
3. A Survey on Efficient Inference for Large Language ModelsarXiv:2404.14294Zixuan Zhou, Xuefei Ning, Ke Hong, et al.2024 · 113 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. Cost-Efficient Large Language Model Serving for Multi-turn Conversations with CachedAttentionUSENIX ATC 2024Bin Gao, Zhuomin He, Puru Sharma, et al.2024 · 105 citations
6. Personal LLM Agents: Insights and Survey about the Capability, Efficiency and SecurityarXiv:2401.05459Yuanchun Li, Hao Wen, Weijun Wang, et al.2024 · 100 citations
7. Small Language Models are the Future of Agentic AIarXiv:2506.02153Peter Belcak, Greg Heinrich, Shizhe Diao, et al.2025 · 92 citations
8. LLM Inference Unveiled: Survey and Roofline Model InsightsarXiv 2024Zhihang Yuan, Yuzhang Shang, Yang Zhou, et al.2024 · 91 citations
9. Small Language Models: Survey, Measurements, and InsightsarXiv:2409.15790Zhenyan Lu, Xiang Li, Dongqi Cai, et al.2024 · 88 citations
10. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
11. Let's Focus on Neuron: Neuron-Level Supervised Fine-tuning for Large Language ModelInternational Conference on Computational Linguistics (COLING)Haoyun Xu, Runzhe Zhan, Yingpeng Ma, et al.2025 · 10 citations
12. Dual Activation-Weight Sparsity: A Training-Free Framework for Efficient Large Language Model CompressionAnnual Meeting of the Association for Computational Linguistics (ACL)Luoyang Sun, Guangyan Li, Cheng Deng, et al.2026

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

This page in Markdown → https://md.research.elamur.ai/free/en/papers/song-2023-powerinfer-fast-large-language-model/cited-by/