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Who cites Alex Krizhevsky

4,603 citations of their works from 4,289 papers of our library (of the 149,439 whose bibliographies we read) · 472 with a page here, the most cited first · page 3 of 5 · 201–300 · ← Alex Krizhevsky

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  1. 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
  2. RobBERT: a Dutch RoBERTa-based Language ModelarXiv:2001.06286Pieter Delobelle, Thomas Winters, Bettina Berendt2020 · 349 citations
  3. Visualizing and Measuring the Geometry of BERTarXiv:1906.02715Andy Coenen, Emily Reif, Ann Yuan, et al.2019 · 349 citations
  4. Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four MinutesarXiv:1807.11205Xianyan Jia, Shutao Song, Wei He, et al.2018 · 348 citations
  5. Sentence Compression by Deletion with LSTMsConference on Empirical Methods in Natural Language Processing (EMNLP)Katja Filippova, Enrique Alfonseca, Carlos A. Colmenares, et al.2015 · 338 citations
  6. ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and GenerationarXiv:2107.02137Yu Sun, Shuohuan Wang, Shikun Feng, et al.2021 · 332 citations
  7. Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning AbstractionsarXiv:1802.04730Nicolas Vasilache, Oleksandr Zinenko, Theodoros Theodoridis, et al.2018 · 323 citations
  8. Learning to Mine Aligned Code and Natural Language Pairs from Stack OverflowarXiv:1805.08949Pengcheng Yin, Bowen Deng, Edgar Chen, et al.2018 · 308 citations
  9. How to Construct Deep Recurrent Neural NetworksarXiv:1312.6026Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, et al.2013 · 302 citations
  10. Overcoming Catastrophic Forgetting by Incremental Moment MatchingarXiv:1703.08475Sang-Woo Lee, Jin-Hwa Kim, Jaehyun Jun, et al.2017 · 298 citations
  11. Analysing Mathematical Reasoning Abilities of Neural ModelsarXiv:1904.01557David Saxton, Edward Grefenstette, Felix Hill, et al.2019 · 288 citations
  12. Hierarchical Multiscale Recurrent Neural NetworksarXiv:1609.01704Junyoung Chung, Sungjin Ahn, Yoshua Bengio2016 · 288 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. Logic Tensor NetworksArtificial IntelligenceSamy Badreddine, Artur d'Avila Garcez, Luciano Serafini, et al.2020 · 276 citations
  16. Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency AnalysisACM Computing Surveys 2019Tal Ben-Nun, Torsten Hoefler2018 · 275 citations
  17. Perceiver: General Perception with Iterative AttentionarXiv:2103.03206Andrew Jaegle, Felix Gimeno, Andrew Brock, et al.2021 · 269 citations
  18. Learning to Optimize Tensor ProgramsarXiv:1805.08166Tianqi Chen, Lianmin Zheng, Eddie Yan, et al.2019 · 269 citations
  19. Membership Inference Attacks against Machine Learning ModelsarXiv:1610.05820Reza Shokri, Marco Stronati, Congzheng Song, et al.2016 · 259 citations
  20. Long-term Recurrent Convolutional Networks for Visual Recognition and DescriptionarXiv:1411.4389Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach, et al.2014 · 245 citations
  21. A simple but tough-to-beat baseline for the Fake News Challenge stance detection taskarXiv:1707.03264Benjamin Riedel, Isabelle Augenstein, Georgios P. Spithourakis, et al.2017 · 242 citations
  22. Generative Language Modeling for Automated Theorem ProvingarXiv:2009.03393Stanislas Polu, Ilya Sutskever2020 · 241 citations
  23. FigureQA: An Annotated Figure Dataset for Visual ReasoningarXiv:1710.07300Samira Ebrahimi Kahou, Vincent Michalski, Adam Atkinson, et al.2017 · 240 citations
  24. Concrete Problems in AI SafetyarXiv:1606.06565Dario Amodei, Chris Olah, Jacob Steinhardt, et al.2016 · 232 citations
  25. A Diagram Is Worth A Dozen ImagesarXiv:1603.07396Aniruddha Kembhavi, Mike Salvato, Eric Kolve, et al.2016 · 231 citations
  26. Progress measures for grokking via mechanistic interpretabilityarXiv:2301.05217Neel Nanda, Lawrence Chan, Tom Lieberum, et al.2023 · 228 citations
  27. Scalable agent alignment via reward modeling: a research directionarXiv:1811.07871Jan Leike, David Krueger, Tom Everitt, et al.2018 · 227 citations
  28. Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free LuncharXiv:2311.03099Le Yu, Bowen Yu, Haiyang Yu, et al.2023 · 217 citations
  29. Mesh-TensorFlow: Deep Learning for SupercomputersarXiv:1811.02084Noam Shazeer, Youlong Cheng, Niki Parmar, et al.2018 · 203 citations
  30. IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian LanguagesarXiv:2305.16307Jay Gala, Pranjal A. Chitale, Raghavan AK, et al.2023 · 200 citations
  31. A Convolutional Attention Network for Extreme Summarization of Source CodearXiv:1602.03001Miltiadis Allamanis, Hao Peng, Charles Sutton2016 · 198 citations
  32. Representation of Linguistic Form and Function in Recurrent Neural NetworksComputational LinguisticsÁkos Kádár, Grzegorz Chrupała, Afra Alishahi2017 · 192 citations
  33. Grounded Language Learning in a Simulated 3D WorldarXiv:1706.06551Karl Moritz Hermann, Felix Hill, Simon Green, et al.2017 · 190 citations
  34. Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training WorkloadsarXiv:1901.05758Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, et al.2019 · 179 citations
  35. Grokking: Generalization Beyond Overfitting on Small Algorithmic DatasetsarXiv:2201.02177Alethea Power, Yuri Burda, Harri Edwards, et al.2022 · 177 citations
  36. Order-Embeddings of Images and LanguagearXiv:1511.06361Ivan Vendrov, Ryan Kiros, Sanja Fidler, et al.2015 · 177 citations
  37. Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak SupervisionarXiv:2312.09390Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.2023 · 172 citations

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