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Noam M. Shazeer
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2020 – today
- 2023
[j6]Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel:
PaLM: Scaling Language Modeling with Pathways. J. Mach. Learn. Res. 24: 240:1-240:113 (2023)- [j5]Adam Roberts, Hyung Won Chung, Gaurav Mishra, Anselm Levskaya, James Bradbury, Daniel Andor, Sharan Narang, Brian Lester, Colin Gaffney, Afroz Mohiuddin, Curtis Hawthorne, Aitor Lewkowycz, Alex Salcianu, Marc van Zee, Jacob Austin, Sebastian Goodman, Livio Baldini Soares, Haitang Hu, Sasha Tsvyashchenko, Aakanksha Chowdhery, Jasmijn Bastings, Jannis Bulian, Xavier Garcia, Jianmo Ni, Andrew Chen, Kathleen Kenealy, Kehang Han, Michelle Casbon, Jonathan H. Clark, Stephan Lee, Dan Garrette, James Lee-Thorp, Colin Raffel, Noam Shazeer, Marvin Ritter, Maarten Bosma, Alexandre Passos, Jeremy Maitin-Shepard, Noah Fiedel, Mark Omernick, Brennan Saeta, Ryan Sepassi, Alexander Spiridonov, Joshua Newlan, Andrea Gesmundo:
Scaling Up Models and Data with t5x and seqio. J. Mach. Learn. Res. 24: 377:1-377:8 (2023) - 2022
- [j4]William Fedus, Barret Zoph, Noam Shazeer:
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity. J. Mach. Learn. Res. 23: 120:1-120:39 (2022) - [i36]Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Kathleen S. Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Agüera y Arcas, Claire Cui, Marian Croak, Ed H. Chi, Quoc Le:
LaMDA: Language Models for Dialog Applications. CoRR abs/2201.08239 (2022) - [i35]Barret Zoph, Irwan Bello, Sameer Kumar, Nan Du, Yanping Huang, Jeff Dean, Noam Shazeer, William Fedus:
Designing Effective Sparse Expert Models. CoRR abs/2202.08906 (2022) - [i34]Adam Roberts, Hyung Won Chung, Anselm Levskaya, Gaurav Mishra, James Bradbury, Daniel Andor, Sharan Narang, Brian Lester, Colin Gaffney, Afroz Mohiuddin, Curtis Hawthorne, Aitor Lewkowycz, Alex Salcianu, Marc van Zee, Jacob Austin, Sebastian Goodman, Livio Baldini Soares, Haitang Hu, Sasha Tsvyashchenko, Aakanksha Chowdhery, Jasmijn Bastings, Jannis Bulian, Xavier Garcia, Jianmo Ni, Andrew Chen, Kathleen Kenealy, Jonathan H. Clark, Stephan Lee, Dan Garrette, James Lee-Thorp, Colin Raffel, Noam Shazeer, Marvin Ritter, Maarten Bosma, Alexandre Passos, Jeremy Maitin-Shepard, Noah Fiedel, Mark Omernick, Brennan Saeta, Ryan Sepassi, Alexander Spiridonov, Joshua Newlan, Andrea Gesmundo:
Scaling Up Models and Data with t5x and seqio. CoRR abs/2203.17189 (2022) - [i33]Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel:
PaLM: Scaling Language Modeling with Pathways. CoRR abs/2204.02311 (2022) - 2021
- [c26]Sharan Narang, Hyung Won Chung, Yi Tay, Liam Fedus, Thibault Févry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, Colin Raffel:
Do Transformer Modifications Transfer Across Implementations and Applications? EMNLP (1) 2021: 5758-5773 - [c25]Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, Zhifeng Chen:
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding. ICLR 2021 - [c24]David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le:
Searching for Efficient Transformers for Language Modeling. NeurIPS 2021: 6010-6022 - [i32]William Fedus, Barret Zoph, Noam Shazeer:
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity. CoRR abs/2101.03961 (2021) - [i31]Sharan Narang, Hyung Won Chung, Yi Tay, William Fedus, Thibault Févry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, Colin Raffel:
Do Transformer Modifications Transfer Across Implementations and Applications? CoRR abs/2102.11972 (2021) - [i30]Yuanzhong Xu, HyoukJoong Lee, Dehao Chen, Blake A. Hechtman, Yanping Huang, Rahul Joshi, Maxim Krikun, Dmitry Lepikhin, Andy Ly, Marcello Maggioni, Ruoming Pang, Noam Shazeer, Shibo Wang, Tao Wang, Yonghui Wu, Zhifeng Chen:
GSPMD: General and Scalable Parallelization for ML Computation Graphs. CoRR abs/2105.04663 (2021) - [i29]David R. So, Wojciech Manke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V. Le:
Primer: Searching for Efficient Transformers for Language Modeling. CoRR abs/2109.08668 (2021) - 2020
- [j3]Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu:
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. J. Mach. Learn. Res. 21: 140:1-140:67 (2020) - [c23]Adam Roberts, Colin Raffel, Noam Shazeer:
How Much Knowledge Can You Pack Into the Parameters of a Language Model? EMNLP (1) 2020: 5418-5426 - [i28]Ciprian Chelba, Mia Xu Chen, Ankur Bapna, Noam Shazeer:
Faster Transformer Decoding: N-gram Masked Self-Attention. CoRR abs/2001.04589 (2020) - [i27]Noam Shazeer:
GLU Variants Improve Transformer. CoRR abs/2002.05202 (2020) - [i26]Adam Roberts, Colin Raffel, Noam Shazeer:
How Much Knowledge Can You Pack Into the Parameters of a Language Model? CoRR abs/2002.08910 (2020) - [i25]Noam Shazeer, Zhenzhong Lan, Youlong Cheng, Nan Ding, Le Hou:
Talking-Heads Attention. CoRR abs/2003.02436 (2020) - [i24]Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, Zhifeng Chen:
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding. CoRR abs/2006.16668 (2020)
2010 – 2019
- 2019
- [c22]Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Ian Simon, Curtis Hawthorne, Noam Shazeer, Andrew M. Dai, Matthew D. Hoffman, Monica Dinculescu, Douglas Eck:
Music Transformer: Generating Music with Long-Term Structure. ICLR (Poster) 2019 - [c21]Jared Lichtarge, Chris Alberti, Shankar Kumar, Noam Shazeer, Niki Parmar, Simon Tong:
Corpora Generation for Grammatical Error Correction. NAACL-HLT (1) 2019: 3291-3301 - [i23]Jared Lichtarge, Christopher Alberti, Shankar Kumar, Noam Shazeer, Niki Parmar, Simon Tong:
Corpora Generation for Grammatical Error Correction. CoRR abs/1904.05780 (2019) - [i22]Le Hou, Youlong Cheng, Noam Shazeer, Niki Parmar, Yeqing Li, Panagiotis Korfiatis, Travis M. Drucker, Daniel J. Blezek, Xiaodan Song:
High Resolution Medical Image Analysis with Spatial Partitioning. CoRR abs/1909.03108 (2019) - [i21]Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu:
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. CoRR abs/1910.10683 (2019) - [i20]Noam Shazeer:
Fast Transformer Decoding: One Write-Head is All You Need. CoRR abs/1911.02150 (2019) - 2018
- [c20]Mia Xu Chen, Orhan Firat, Ankur Bapna, Melvin Johnson, Wolfgang Macherey, George F. Foster, Llion Jones, Mike Schuster, Noam Shazeer, Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Zhifeng Chen, Yonghui Wu, Macduff Hughes:
The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation. ACL (1) 2018: 76-86 - [c19]Ashish Vaswani, Samy Bengio, Eugene Brevdo, François Chollet, Aidan N. Gomez, Stephan Gouws, Llion Jones, Lukasz Kaiser, Nal Kalchbrenner, Niki Parmar, Ryan Sepassi, Noam Shazeer, Jakob Uszkoreit:
Tensor2Tensor for Neural Machine Translation. AMTA (1) 2018: 193-199 - [c18]Ravi Teja Mullapudi, William R. Mark, Noam Shazeer, Kayvon Fatahalian:
HydraNets: Specialized Dynamic Architectures for Efficient Inference. CVPR 2018: 8080-8089 - [c17]Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, Noam Shazeer:
Generating Wikipedia by Summarizing Long Sequences. ICLR (Poster) 2018 - [c16]Lukasz Kaiser, Samy Bengio, Aurko Roy, Ashish Vaswani, Niki Parmar, Jakob Uszkoreit, Noam Shazeer:
Fast Decoding in Sequence Models Using Discrete Latent Variables. ICML 2018: 2395-2404 - [c15]Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, Dustin Tran:
Image Transformer. ICML 2018: 4052-4061 - [c14]Noam Shazeer, Mitchell Stern:
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost. ICML 2018: 4603-4611 - [c13]Mitchell Stern, Noam Shazeer, Jakob Uszkoreit:
Blockwise Parallel Decoding for Deep Autoregressive Models. NeurIPS 2018: 10107-10116 - [c12]Noam Shazeer, Youlong Cheng, Niki Parmar, Dustin Tran, Ashish Vaswani, Penporn Koanantakool, Peter Hawkins, HyoukJoong Lee, Mingsheng Hong, Cliff Young, Ryan Sepassi, Blake A. Hechtman:
Mesh-TensorFlow: Deep Learning for Supercomputers. NeurIPS 2018: 10435-10444 - [i19]Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, Noam Shazeer:
Generating Wikipedia by Summarizing Long Sequences. CoRR abs/1801.10198 (2018) - [i18]Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku:
Image Transformer. CoRR abs/1802.05751 (2018) - [i17]Lukasz Kaiser, Aurko Roy, Ashish Vaswani, Niki Parmar, Samy Bengio, Jakob Uszkoreit, Noam Shazeer:
Fast Decoding in Sequence Models using Discrete Latent Variables. CoRR abs/1803.03382 (2018) - [i16]Ashish Vaswani, Samy Bengio, Eugene Brevdo, François Chollet, Aidan N. Gomez, Stephan Gouws, Llion Jones, Lukasz Kaiser, Nal Kalchbrenner, Niki Parmar, Ryan Sepassi, Noam Shazeer, Jakob Uszkoreit:
Tensor2Tensor for Neural Machine Translation. CoRR abs/1803.07416 (2018) - [i15]Noam Shazeer, Mitchell Stern:
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost. CoRR abs/1804.04235 (2018) - [i14]Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Noam Shazeer, Curtis Hawthorne, Andrew M. Dai, Matthew D. Hoffman, Douglas Eck:
An Improved Relative Self-Attention Mechanism for Transformer with Application to Music Generation. CoRR abs/1809.04281 (2018) - [i13]Jared Lichtarge, Christopher Alberti, Shankar Kumar, Noam Shazeer, Niki Parmar:
Weakly Supervised Grammatical Error Correction using Iterative Decoding. CoRR abs/1811.01710 (2018) - [i12]Noam Shazeer, Youlong Cheng, Niki Parmar, Dustin Tran, Ashish Vaswani, Penporn Koanantakool, Peter Hawkins, HyoukJoong Lee, Mingsheng Hong, Cliff Young, Ryan Sepassi, Blake A. Hechtman:
Mesh-TensorFlow: Deep Learning for Supercomputers. CoRR abs/1811.02084 (2018) - [i11]Mitchell Stern, Noam Shazeer, Jakob Uszkoreit:
Blockwise Parallel Decoding for Deep Autoregressive Models. CoRR abs/1811.03115 (2018) - 2017
- [c11]Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, Jeff Dean:
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. ICLR (Poster) 2017 - [c10]Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin:
Attention is All you Need. NIPS 2017: 5998-6008 - [i10]Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, Jeff Dean:
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. CoRR abs/1701.06538 (2017) - [i9]Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser
, Illia Polosukhin:
Attention Is All You Need. CoRR abs/1706.03762 (2017) - [i8]Lukasz Kaiser, Aidan N. Gomez, Noam Shazeer, Ashish Vaswani, Niki Parmar, Llion Jones, Jakob Uszkoreit:
One Model To Learn Them All. CoRR abs/1706.05137 (2017) - 2016
- [j2]Joris Pelemans, Noam Shazeer, Ciprian Chelba:
Sparse Non-negative Matrix Language Modeling. Trans. Assoc. Comput. Linguistics 4: 329-342 (2016) - [c9]Georg Heigold, Ignacio Moreno, Samy Bengio, Noam Shazeer:
End-to-end text-dependent speaker verification. ICASSP 2016: 5115-5119 - [c8]Babak Damavandi, Shankar Kumar, Noam Shazeer, Antoine Bruguier:
NN-Grams: Unifying Neural Network and n-Gram Language Models for Speech Recognition. INTERSPEECH 2016: 3499-3503 - [i7]Noam Shazeer, Ryan Doherty, Colin Evans, Chris Waterson:
Swivel: Improving Embeddings by Noticing What's Missing. CoRR abs/1602.02215 (2016) - [i6]Rafal Józefowicz, Oriol Vinyals, Mike Schuster, Noam Shazeer, Yonghui Wu:
Exploring the Limits of Language Modeling. CoRR abs/1602.02410 (2016) - [i5]Babak Damavandi, Shankar Kumar, Noam Shazeer, Antoine Bruguier:
NN-grams: Unifying neural network and n-gram language models for Speech Recognition. CoRR abs/1606.07470 (2016) - 2015
- [c7]Ciprian Chelba, Noam Shazeer:
Sparse non-negative matrix language modeling for geo-annotated query session data. ASRU 2015: 8-14 - [c6]Noam Shazeer, Joris Pelemans, Ciprian Chelba:
Sparse non-negative matrix language modeling for skip-grams. INTERSPEECH 2015: 1428-1432 - [c5]Joris Pelemans, Noam Shazeer, Ciprian Chelba:
Pruning sparse non-negative matrix n-gram language models. INTERSPEECH 2015: 1433-1437 - [c4]Samy Bengio, Oriol Vinyals, Navdeep Jaitly, Noam Shazeer:
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks. NIPS 2015: 1171-1179 - [i4]Samy Bengio, Oriol Vinyals, Navdeep Jaitly, Noam Shazeer:
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks. CoRR abs/1506.03099 (2015) - [i3]Georg Heigold, Ignacio Moreno, Samy Bengio, Noam Shazeer:
End-to-End Text-Dependent Speaker Verification. CoRR abs/1509.08062 (2015) - 2014
- [i2]Noam Shazeer, Joris Pelemans, Ciprian Chelba:
Skip-gram Language Modeling Using Sparse Non-negative Matrix Probability Estimation. CoRR abs/1412.1454 (2014) - 2010
- [i1]Georges Harik, Noam Shazeer:
Variational Program Inference. CoRR abs/1006.0991 (2010)
2000 – 2009
- 2002
- [j1]Michael L. Littman, Greg A. Keim, Noam M. Shazeer:
A probabilistic approach to solving crossword puzzles. Artif. Intell. 134(1-2): 23-55 (2002)
1990 – 1999
- 1999
- [c3]Noam M. Shazeer, Michael L. Littman, Greg A. Keim:
Solving Crossword Puzzles as Probabilistic Constraint Satisfaction. AAAI/IAAI 1999: 156-162 - [c2]Greg A. Keim, Noam M. Shazeer, Michael L. Littman, Sushant Agarwal, Catherine M. Cheves, Joseph Fitzgerald, Jason Grosland, Fan Jiang, Shannon Pollard, Karl Weinmeister:
PROVERB: The Probabilistic Cruciverbalist. AAAI/IAAI 1999: 710-717 - [c1]Michael L. Littman, Greg A. Keim, Noam M. Shazeer:
Solving Crosswords with PROVERB. AAAI/IAAI 1999: 914-915
Coauthor Index
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