🔗 Who cites «PipeDream: Fast and Efficient Pipeline Parallel DNN Training»

74 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · ← back to «PipeDream: Fast and Efficient Pipeline Parallel DNN Training»

1. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
2. GPT-NeoX-20B: An Open-Source Autoregressive Language ModelBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsSidney Black, Stella Biderman, Eric Hallahan, et al.2022 · 831 citations
3. Kimi K2: Open Agentic IntelligencearXiv:2507.20534Kimi Team, Yifan Bai, Yiping Bao, et al.2025 · 347 citations
4. ZeRO-Offload: Democratizing Billion-Scale Model TrainingarXiv:2101.06840Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, et al.2021 · 309 citations
5. ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep LearningSC 2021Samyam Rajbhandari, Olatunji Ruwase, Jeff Rasley, et al.2021 · 254 citations
6. 8-bit Optimizers via Block-wise QuantizationarXiv:2110.02861Tim Dettmers, Mike Lewis, Sam Shleifer, et al.2021 · 181 citations
7. Memory-Efficient Pipeline-Parallel DNN TrainingInternational Conference on Machine Learning (ICML)Deepak Narayanan, Amar Phanishayee, Kaiyu Shi, et al.2020 · 153 citations
8. DAPPLE: A Pipelined Data Parallel Approach for Training Large ModelsarXiv:2007.01045Shiqing Fan, Yi Rong, Chen Meng, et al.2020 · 107 citations
9. ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and GenerationarXiv:2112.12731Shuohuan Wang, Yu Sun, Yang Xiang, et al.2021 · 63 citations
10. EfficientTool: A Cost-Effective Aligning Framework for Tool-Conditioned Agents in SME ScenariosAnnual Meeting of the Association for Computational Linguistics (ACL)Yuanqi Mu, Bingfeng Pi, Defei Xia, et al.2026

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

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