🧑‍🔬 Barret Zoph — all works

43 works · ← Barret Zoph

1. Learning Transferable Architectures for Scalable Image RecognitionIEEE Computer Society Conference on Computer Vision and Pattern RecognitionBarret Zoph, Vijay Vasudevan, Jonathon Shlens, et al.2017 · 6,583 citations
2. Neural Architecture Search with Reinforcement LearningarXiv:1611.01578Barret Zoph, Quoc V. Le2016 · 4,413 citations
3. SpecAugment: A Simple Data Augmentation Method for Automatic Speech RecognitionInterspeechDaniel S. Park, William Chan, Yu Zhang, et al.2019 · 3,837 citations
4. Scaling Instruction-Finetuned Language Models ↗arXiv:2210.11416 · no summary yetHyung Won Chung et al.2022 · 3,392 citations
5. Randaugment: Practical automated data augmentation with a reduced search space ↗IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · no summary yetEkin D. Cubuk et al.2020 · 3,233 citations
6. AutoAugment: Learning Augmentation Strategies From Data ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetEkin D. Cubuk et al.2019 · 2,810 citations
7. Emergent Abilities of Large Language ModelsarXiv:2206.07682Jason Wei, Yi Tay, Rishi Bommasani, et al.2022 · 2,269 citations
8. Progressive Neural Architecture Search ↗Lecture notes in computer science · no summary yetChenxi Liu et al.2018 · 2,023 citations
9. Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity ↗arXiv:2101.03961 · no summary yetWilliam Fedus, Barret Zoph, Noam Shazeer2021 · 1,271 citations
10. Attention Augmented Convolutional Networks ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetIrwan Bello et al.2019 · 1,246 citations
11. Efficient Neural Architecture Search via Parameters Sharing ↗International Conference on Machine Learning · no summary yetHieu Pham et al.2018 · 1,209 citations
12. Transfer Learning for Low-Resource Neural Machine Translation ↗Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing · no summary yetBarret Zoph et al.2016 · 1,185 citations
13. Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetGolnaz Ghiasi et al.2021 · 1,178 citations
14. Searching for Activation Functions ↗arXiv:1710.05941 · no summary yetPrajit Ramachandran, Barret Zoph, Quoc V. Le2017 · 856 citations
15. AutoAugment: Learning Augmentation Policies from Data ↗arXiv (Cornell University) · no summary yetEkin D. Cubuk et al.2018 · 726 citations
16. Efficient Neural Architecture Search via Parameter Sharing ↗arXiv:1802.03268 · no summary yetHieu Pham et al.2018 · 699 citations
17. The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 607 citations
18. AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty ↗arXiv (Cornell University) · no summary yetDan Hendrycks et al.2019 · 588 citations
19. Learning Data Augmentation Strategies for Object Detection ↗Lecture notes in computer science · no summary yetBarret Zoph et al.2020 · 587 citations
20. Understanding and Simplifying One-Shot Architecture Search ↗International Conference on Machine Learning · no summary yetGabriel Bender et al.2018 · 515 citations
21. GLaM: Efficient Scaling of Language Models with Mixture-of-ExpertsarXiv:2112.06905Nan Du, Yanping Huang, Andrew M. Dai, et al.2021 · 496 citations
22. Multi-Source Neural TranslationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Barret Zoph, Kevin Knight2016 · 435 citations
23. Rethinking Pre-training and Self-training ↗arXiv (Cornell University) · no summary yetBarret Zoph et al.2020 · 428 citations
24. Searching for Efficient Multi-Scale Architectures for Dense Image Prediction ↗arXiv (Cornell University) · no summary yetLiang-Chieh Chen et al.2018 · 335 citations
25. Neural Optimizer Search with Reinforcement Learning ↗arXiv (Cornell University) · no summary yetIrwan Bello et al.2017 · 263 citations
26. Revisiting ResNets: Improved Training and Scaling Strategies ↗arXiv (Cornell University) · no summary yetIrwan Bello et al.2021 · 221 citations
27. ST-MoE: Designing Stable and Transferable Sparse Expert Models ↗arXiv:2202.08906 · no summary yetBarret Zoph et al.2022 · 205 citations
28. Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation ↗Lecture notes in computer science · no summary yetLiang-Chieh Chen et al.2020 · 161 citations
29. A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity ↗arXiv:2305.13169 · no summary yetShayne Longpre et al.2023 · 104 citations
30. Multi-Task Self-Training for Learning General Representations ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetGolnaz Ghiasi et al.2021 · 86 citations
31. A Review of Sparse Expert Models in Deep Learning ↗arXiv (Cornell University) · no summary yetW. Fedus, Jeff Dean, Barret Zoph2022 · 82 citations
32. Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language ModelsarXiv:2305.14705Sheng Shen, Le Hou, Yanqi Zhou, et al.2023 · 70 citations
33. Improving 3D Object Detection Through Progressive Population Based Augmentation ↗Lecture notes in computer science · no summary yetShuyang Cheng et al.2020 · 67 citations
34. Simple, Fast Noise-Contrastive Estimation for Large RNN Vocabularies ↗Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetBarret Zoph et al.2016 · 45 citations
35. Simple Training Strategies and Model Scaling for Object Detection ↗arXiv (Cornell University) · no summary yetXianzhi Du et al.2021 · 29 citations
36. Intriguing Properties of Adversarial Examples ↗arXiv (Cornell University) · no summary yetEkin D. Cubuk et al.2017 · 28 citations
37. Faster Discovery of Neural Architectures by Searching for Paths in a Large Model ↗International Conference on Learning Representations · no summary yetHieu Pham et al.2018 · 15 citations
38. How Much Information Does a Human Translator Add to the Original? ↗Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing · no summary yetBarret Zoph, Marjan Ghazvininejad, Kevin Knight2015 · 9 citations
39. Backprop Evolution ↗arXiv (Cornell University) · no summary yetMaximilian Alber et al.2018 · 7 citations
40. Does Data Augmentation Benefit from Split BatchNorms ↗arXiv (Cornell University) · no summary yetAmil Merchant, Barret Zoph, Ekin D. Cubuk2020 · 4 citations
41. EXPLORING NEURAL ARCHITECTURE SEARCH FOR LANGUAGE TASKS ↗no summary yetMinh-Thang Luong et al.2018 · 3 citations
42. Revisiting ResNets: Improved Training Methodologies and Scaling Principles ↗no summary yetIrwan Bello et al.2021 · 1 citation
43. スケーラブル画像認識のための移動可能アーキテクチャの学習【JST・京大機械翻訳】 ↗IEEE Conference Proceedings · no summary yetBarret Zoph et al.2018

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