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Who cites Cliff Young

1,978 citations of their works from 1,955 papers of our library (of the 149,439 whose bibliographies we read) · 329 with a page here, the most cited first · page 2 of 4 · 101–200 · ← Cliff Young

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  1. Training Tips for the Transformer ModelarXiv:1804.00247 · The Prague Bulletin of Mathematical Linguistics 110, April 2018, pp. 43-70Martin Popel, Ondřej Bojar2018 · 370 citations
  2. Exploring Neural Text Simplification ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Sergiu Nisioi, Sanja Štajner, Simone Paolo Ponzetto, et al.2017 · 353 citations
  3. PyTorch Distributed: Experiences on Accelerating Data Parallel TrainingarXiv:2006.15704Shen Li, Yanli Zhao, Rohan Varma, et al.2020 · 348 citations
  4. An Actor-Critic Algorithm for Sequence PredictionarXiv:1607.07086Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, et al.2016 · 335 citations
  5. Generating Wikipedia by Summarizing Long SequencesarXiv:1801.10198Peter J. Liu, Mohammad Saleh, Etienne Pot, et al.2018 · 334 citations
  6. A Transformer-based approach to Irony and Sarcasm detectionNeural Computing and ApplicationsRolandos Alexandros Potamias, Georgios Siolas, Andreas - Georgios Stafylopatis2019 · 312 citations
  7. S2ORC: The Semantic Scholar Open Research CorpusarXiv:1911.02782Kyle Lo, Lucy Lu Wang, Mark Neumann, et al.2019 · 312 citations
  8. ZeRO-Offload: Democratizing Billion-Scale Model TrainingarXiv:2101.06840Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, et al.2021 · 309 citations
  9. UDPipe 2.0 Prototype at CoNLL 2018 UD Shared TaskMilan Straka2018 · 303 citations
  10. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
  11. Survey: Multiword Expression Processing: A SurveyComputational LinguisticsMathieu Constant, Gülşen Eryiǧit, Johanna Monti, et al.2017 · 296 citations
  12. ReClor: A Reading Comprehension Dataset Requiring Logical ReasoningarXiv:2002.04326Weihao Yu, Zihang Jiang, Yanfei Dong, et al.2020 · 286 citations
  13. Beyond Data and Model Parallelism for Deep Neural NetworksSysML 2019Zhihao Jia, Matei Zaharia, Alex Aiken2018 · 280 citations
  14. Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep LearningOSDI 2022Lianmin Zheng, Zhuohan Li, Hao Zhang, et al.2022 · 279 citations
  15. Reducing Activation Recomputation in Large Transformer ModelsarXiv:2205.05198Vijay Korthikanti, Jared Casper, Sangkug Lym, et al.2022 · 273 citations
  16. Contrastive Decoding: Open-ended Text Generation as OptimizationarXiv:2210.15097Xiang Lisa Li, Ari Holtzman, Daniel Fried, et al.2022 · 254 citations
  17. ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep LearningSC 2021Samyam Rajbhandari, Olatunji Ruwase, Jeff Rasley, et al.2021 · 254 citations
  18. Generative Language Modeling for Automated Theorem ProvingarXiv:2009.03393Stanislas Polu, Ilya Sutskever2020 · 241 citations
  19. The University of Edinburgh's Neural MT Systems for WMT17Conference on Machine Translation (WMT)Rico Sennrich, Alexandra Birch, Anna Currey, et al.2017 · 228 citations
  20. Correcting Length Bias in Neural Machine TranslationarXiv:1808.10006Kenton Murray, David Chiang2018 · 221 citations
  21. Neural Arabic Question AnsweringArabic Natural Language Processing Workshop (WANLP)Hussein Mozannar, Elie Maamary, Karl El Hajal, et al.2019 · 206 citations
  22. Does Neural Machine Translation Benefit from Larger Context?arXiv:1704.05135Sebastien Jean, Stanislas Lauly, Orhan Firat, et al.2017 · 201 citations
  23. Charformer: Fast Character Transformers via Gradient-based Subword TokenizationarXiv:2106.12672Yi Tay, Vinh Q. Tran, Sebastian Ruder, et al.2021 · 186 citations
  24. Representation Degeneration Problem in Training Natural Language Generation ModelsarXiv:1907.12009Jun Gao, Di He, Xu Tan, et al.2019 · 181 citations
  25. StructBERT: Incorporating Language Structures into Pre-training for Deep Language UnderstandingarXiv:1908.04577Wei Wang, Bin Bi, Ming Yan, et al.2019 · 175 citations
  26. Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy OptimizationarXiv:2210.01241Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kiante Brantley, et al.2022 · 174 citations
  27. AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning ServingOSDI 2023Zhuohan Li, Lianmin Zheng, Yinmin Zhong, et al.2023 · 170 citations
  28. A Comprehensive Exploration on WikiSQL with Table-Aware Word ContextualizationarXiv:1902.01069Wonseok Hwang, Jinyeong Yim, Seunghyun Park, et al.2019 · 170 citations
  29. PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel ComputationarXiv:2104.12369Wei Zeng, Xiaozhe Ren, Teng Su, et al.2021 · 161 citations
  30. Locally Typical SamplingTransactions of the Association for Computational Linguistics (TACL)Clara Meister, Tiago Pimentel, Gian Wiher, et al.2023 · 157 citations
  31. Pre-Training BERT on Arabic Tweets: Practical ConsiderationsarXiv:2102.10684Ahmed Abdelali, Sabit Hassan, Hamdy Mubarak, et al.2021 · 150 citations
  32. Beyond Human Data: Scaling Self-Training for Problem-Solving with Language ModelsarXiv:2312.06585Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.2023 · 147 citations
  33. Rethinking embedding coupling in pre-trained language modelsarXiv:2010.12821Hyung Won Chung, Thibault Févry, Henry Tsai, et al.2020 · 142 citations
  34. SLiC-HF: Sequence Likelihood Calibration with Human FeedbackarXiv:2305.10425Yao Zhao, Rishabh Joshi, Tianqi Liu, et al.2023 · 141 citations
  35. CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding TasksarXiv:2105.12655Ruchir Puri, David S. Kung, Geert Janssen, et al.2021 · 141 citations
  36. Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and ApproachesarXiv:1904.01172Shane Storks, Qiaozi Gao, Joyce Y. Chai2019 · 135 citations

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