PyTorch: An imperative style, high-performance deep learning library A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
Advances in Neural Information Processing Systems, 8024-8035, 2019
53032 2019 PaLM: Scaling Language Modeling with Pathways A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ...
arXiv preprint arXiv:2204.02311, 2022
5604 2022 JAX: composable transformations of Python+NumPy programs J Bradbury, R Frostig, P Hawkins, MJ Johnson, C Leary, D Maclaurin, ...
https://github.com/google/jax, 18, 2018
3114 2018 Pointer Sentinel Mixture Models S Merity, C Xiong, J Bradbury, R Socher
ICLR 2017, 2016
2586 2016 Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
2488 2023 Ask me anything: Dynamic memory networks for natural language processing A Kumar, O Irsoy, P Ondruska, M Iyyer, J Bradbury, I Gulrajani, V Zhong, ...
ICML 2016, 2016
1598 2016 Palm 2 technical report R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ...
arXiv preprint arXiv:2305.10403, 2023
1561 2023 Learned in Translation: Contextualized Word Vectors B McCann, J Bradbury, C Xiong, R Socher
NIPS 2017, 2017
1321 2017 Scaling language models: Methods, analysis & insights from training gopher JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ...
arXiv preprint arXiv:2112.11446, 2021
1147 2021 Non-Autoregressive Neural Machine Translation J Gu, J Bradbury, C Xiong, VOK Li, R Socher
ICLR 2018, 2018
893 2018 PaLI: A Jointly-Scaled Multilingual Language-Image Model X Chen, X Wang, S Changpinyo, AJ Piergiovanni, P Padlewski, D Salz, ...
arXiv preprint arXiv:2209.06794, 2022
679 2022 Quasi-Recurrent Neural Networks J Bradbury, S Merity, C Xiong, R Socher
ICLR 2017, 2016
654 2016 Efficiently Scaling Transformer Inference R Pope, S Douglas, A Chowdhery, J Devlin, J Bradbury, A Levskaya, ...
MLSys 2023, 2022
349 2022 OpenSpiel: A framework for reinforcement learning in games M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ...
arXiv preprint arXiv:1908.09453, 2019
301 2019 Scaling Up Models and Data with A Roberts, HW Chung, A Levskaya, G Mishra, J Bradbury, D Andor, ...
arXiv preprint arXiv:2203.17189, 2022
162 * 2022 Velo: Training versatile learned optimizers by scaling up L Metz, J Harrison, CD Freeman, A Merchant, L Beyer, J Bradbury, ...
arXiv preprint arXiv:2211.09760, 2022
72 2022 On Machine Learning and Programming Languages M Innes, S Karpinski, V Shah, D Barber, P Stenetorp, T Besard, ...
SysML 2018, 2018
28 2018 A Flexible Approach to Automated RNN Architecture Generation M Schrimpf, S Merity, J Bradbury, R Socher
ICLR Workshop 2018, 2018
23 2018 Exploring the limits of Concurrency in ML Training on Google TPUs S Kumar, Y Wang, C Young, J Bradbury, N Kumar, D Chen, A Swing
MLSys 2021, 2021
21 2021 MetaMind Neural Machine Translation System for WMT 2016 J Bradbury, R Socher
WMT 2016, 2016
19 2016 
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