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Who cites Arvind Krishnamurthy

902 citations of their works from 780 papers of our library (of the 149,439 whose bibliographies we read) · 45 with a page here, the most cited first · ← Arvind Krishnamurthy

  1. Longformer: The Long-Document TransformerarXiv:2004.05150Iz Beltagy, Matthew E. Peters, Arman Cohan2020 · 3,880 citations
  2. Triton: An Intermediate Language and Compiler for Tiled Neural Network ComputationsMAPL 2019Philippe Tillet, H. T. Kung, David Cox2019 · 729 citations
  3. Orca: A Distributed Serving System for Transformer-Based Generative ModelsOSDI 2022Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, et al.2022 · 478 citations
  4. Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning AbstractionsarXiv:1802.04730Nicolas Vasilache, Oleksandr Zinenko, Theodoros Theodoridis, et al.2018 · 323 citations
  5. Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep LearningOSDI 2022Lianmin Zheng, Zhuohan Li, Hao Zhang, et al.2022 · 279 citations
  6. Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency AnalysisACM Computing Surveys 2019Tal Ben-Nun, Torsten Hoefler2018 · 275 citations
  7. Learning to Optimize Tensor ProgramsarXiv:1805.08166Tianqi Chen, Lianmin Zheng, Eddie Yan, et al.2019 · 269 citations
  8. QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMsConference on Neural Information Processing Systems (NeurIPS)Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al.2024 · 254 citations
  9. KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV CachearXiv:2402.02750Zirui Liu, Jiayi Yuan, Hongye Jin, et al.2024 · 244 citations
  10. Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive SurveyarXiv:2403.14608Zeyu Han, Chao Gao, Jinyang Liu, et al.2024 · 240 citations
  11. Quest: Query-Aware Sparsity for Efficient Long-Context LLM InferencearXiv:2406.10774Jiaming Tang, Yilong Zhao, Kan Zhu, et al.2024 · 203 citations
  12. Atom: Low-bit Quantization for Efficient and Accurate LLM ServingMLSys 2024Yilong Zhao, Chien-Yu Lin, Kan Zhu, et al.2023 · 156 citations
  13. DeepSeek-V4: Towards Highly Efficient Million-Token Context IntelligencearXiv:2606.19348DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.2026 · 122 citations
  14. I-BERT: Integer-only BERT QuantizationInternational Conference on Machine Learning (ICML)Sehoon Kim, Amir Gholami, Zhewei Yao, et al.2021 · 122 citations
  15. QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM ServingMLSys 2025Yujun Lin, Haotian Tang, Shang Yang, et al.2024 · 120 citations
  16. A Survey on Efficient Inference for Large Language ModelsarXiv:2404.14294Zixuan Zhou, Xuefei Ning, Ke Hong, et al.2024 · 113 citations
  17. Efficient Large Language Models: A SurveyarXiv:2312.03863Zhongwei Wan, Xin Wang, Che Liu, et al.2023 · 110 citations
  18. LLM Inference Unveiled: Survey and Roofline Model InsightsarXiv 2024Zhihang Yuan, Yuzhang Shang, Yang Zhou, et al.2024 · 91 citations
  19. Liger Kernel: Efficient Triton Kernels for LLM TrainingarXiv:2410.10989Pin-Lun Hsu, Yun Dai, Vignesh Kothapalli, et al.2024 · 87 citations
  20. Zeus: Understanding and Optimizing GPU Energy Consumption of DNN TrainingarXiv:2208.06102Jie You, Jae-Won Chung, Mosharaf Chowdhury2022 · 82 citations
  21. S-LoRA: Serving Thousands of Concurrent LoRA AdaptersMLSys 2024Ying Sheng, Shiyi Cao, Dacheng Li, et al.2023 · 80 citations
  22. TASO: Optimizing Deep Learning Computation with Automatic Generation of Graph SubstitutionsSOSP 2019Zhihao Jia, Oded Padon, James Thomas, et al.2019 · 72 citations
  23. Kevin: Multi-Turn RL for Generating CUDA KernelsarXiv 2025Carlo Baronio, Pietro Marsella, Ben Pan, et al.2025 · 69 citations
  24. Flex Attention: A Programming Model for Generating Optimized Attention KernelsarXiv:2412.05496Juechu Dong, Boyuan Feng, Driss Guessous, et al.2024 · 55 citations
  25. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
  26. 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

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