PROVERB: The Probabilistic Cruciverbalist. - Greg A. Keim; Noam M. Shazeer; Michael L. Littman; Sushant Agarwal; Catherine M. Cheves; Joseph Fitzgerald; Jason Grosland; Fan Jiang; Shannon Pollard; Karl Weinmeister (AAAI/IAAI, 1999)

Solving Crosswords with PROVERB. - Michael L. Littman; Greg A. Keim; Noam M. Shazeer (AAAI/IAAI, 1999)

Solving Crossword Puzzles as Probabilistic Constraint Satisfaction. - Noam M. Shazeer; Michael L. Littman; Greg A. Keim (AAAI/IAAI, 1999)

A probabilistic approach to solving crossword puzzles. - Michael L. Littman; Greg A. Keim; Noam M. Shazeer (Artif. Intell., 2002)

Variational Program Inference - Georges Harik; Noam Shazeer (CoRR, 2010)

Skip-gram Language Modeling Using Sparse Non-negative Matrix Probability Estimation. - Noam Shazeer; Joris Pelemans; Ciprian Chelba (CoRR, 2014)

Sparse non-negative matrix language modeling for geo-annotated query session data. - Ciprian Chelba; Noam Shazeer (ASRU, 2015)

Pruning sparse non-negative matrix n-gram language models. - Joris Pelemans; Noam Shazeer; Ciprian Chelba (INTERSPEECH, 2015)

Sparse non-negative matrix language modeling for skip-grams. - Noam Shazeer; Joris Pelemans; Ciprian Chelba (INTERSPEECH, 2015)

Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks. - Samy Bengio; Oriol Vinyals; Navdeep Jaitly; Noam Shazeer (NIPS, 2015)

End-to-end text-dependent speaker verification. - Georg Heigold; Ignacio Moreno; Samy Bengio; Noam Shazeer (ICASSP, 2016)

NN-Grams: Unifying Neural Network and n-Gram Language Models for Speech Recognition. - Babak Damavandi; Shankar Kumar; Noam Shazeer; Antoine Bruguier (INTERSPEECH, 2016)

Exploring the Limits of Language Modeling. - Rafal Józefowicz; Oriol Vinyals; Mike Schuster; Noam Shazeer; Yonghui Wu (CoRR, 2016)

Swivel: Improving Embeddings by Noticing What's Missing. - Noam Shazeer; Ryan Doherty; Colin Evans; Chris Waterson (CoRR, 2016)

Sparse Non-negative Matrix Language Modeling. - Joris Pelemans; Noam Shazeer; Ciprian Chelba (Trans. Assoc. Comput. Linguistics, 2016)

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. - Noam Shazeer; Azalia Mirhoseini; Krzysztof Maziarz; Andy Davis; Quoc V. Le; Geoffrey E. Hinton; Jeff Dean (ICLR (Poster), 2017)

Attention is All you Need. - Ashish Vaswani; Noam Shazeer; Niki Parmar; Jakob Uszkoreit; Llion Jones; Aidan N. Gomez; Lukasz Kaiser; Illia Polosukhin (NIPS, 2017)

One Model To Learn Them All. - Lukasz Kaiser; Aidan N. Gomez; Noam Shazeer; Ashish Vaswani; Niki Parmar; Llion Jones; Jakob Uszkoreit (CoRR, 2017)

The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation. - 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; et al. (ACL (1), 2018)

Tensor2Tensor for Neural Machine Translation. - 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; et al. (AMTA (1), 2018)

HydraNets: Specialized Dynamic Architectures for Efficient Inference. - Ravi Teja Mullapudi; William R. Mark; Noam Shazeer; Kayvon Fatahalian (CVPR, 2018)

Generating Wikipedia by Summarizing Long Sequences. - Peter J. Liu; Mohammad Saleh; Etienne Pot; Ben Goodrich; Ryan Sepassi; Lukasz Kaiser; Noam Shazeer (ICLR (Poster), 2018)

Fast Decoding in Sequence Models Using Discrete Latent Variables. - Lukasz Kaiser; Samy Bengio; Aurko Roy; Ashish Vaswani; Niki Parmar; Jakob Uszkoreit; Noam Shazeer (ICML, 2018)

Image Transformer. - Niki Parmar; Ashish Vaswani; Jakob Uszkoreit; Lukasz Kaiser; Noam Shazeer; Alexander Ku; Dustin Tran (ICML, 2018)

Adafactor: Adaptive Learning Rates with Sublinear Memory Cost. - Noam Shazeer; Mitchell Stern (ICML, 2018)

Mesh-TensorFlow: Deep Learning for Supercomputers. - 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 (NeurIPS, 2018)

Blockwise Parallel Decoding for Deep Autoregressive Models. - Mitchell Stern; Noam Shazeer; Jakob Uszkoreit (NeurIPS, 2018)

Image Transformer. - Niki Parmar; Ashish Vaswani; Jakob Uszkoreit; Lukasz Kaiser; Noam Shazeer; Alexander Ku (CoRR, 2018)

An Improved Relative Self-Attention Mechanism for Transformer with Application to Music Generation. - Cheng-Zhi Anna Huang; Ashish Vaswani; Jakob Uszkoreit; Noam Shazeer; Curtis Hawthorne; Andrew M. Dai; Matthew D. Hoffman; Douglas Eck (CoRR, 2018)

Weakly Supervised Grammatical Error Correction using Iterative Decoding. - Jared Lichtarge; Christopher Alberti; Shankar Kumar; Noam Shazeer; Niki Parmar (CoRR, 2018)

Music Transformer: Generating Music with Long-Term Structure. - Cheng-Zhi Anna Huang; Ashish Vaswani; Jakob Uszkoreit; Ian Simon; Curtis Hawthorne; Noam Shazeer; Andrew M. Dai; Matthew D. Hoffman; Monica Dinculescu; Douglas Eck (ICLR (Poster), 2019)

Corpora Generation for Grammatical Error Correction. - Jared Lichtarge; Chris Alberti; Shankar Kumar; Noam Shazeer; Niki Parmar; Simon Tong (NAACL-HLT (1), 2019)

High Resolution Medical Image Analysis with Spatial Partitioning. - Le Hou; Youlong Cheng; Noam Shazeer; Niki Parmar; Yeqing Li; Panagiotis Korfiatis; Travis M. Drucker; Daniel J. Blezek; Xiaodan Song (CoRR, 2019)

Fast Transformer Decoding: One Write-Head is All You Need. - Noam Shazeer (CoRR, 2019)

How Much Knowledge Can You Pack Into the Parameters of a Language Model? - Adam Roberts; Colin Raffel; Noam Shazeer (EMNLP (1), 2020)

Faster Transformer Decoding: N-gram Masked Self-Attention. - Ciprian Chelba; Mia Xu Chen; Ankur Bapna; Noam Shazeer (CoRR, 2020)

GLU Variants Improve Transformer. - Noam Shazeer (CoRR, 2020)

Talking-Heads Attention. - Noam Shazeer; Zhenzhong Lan; Youlong Cheng; Nan Ding 002; Le Hou (CoRR, 2020)

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. - Colin Raffel; Noam Shazeer; Adam Roberts; Katherine Lee; Sharan Narang; Michael Matena; Yanqi Zhou; Wei Li 133; Peter J. Liu (J. Mach. Learn. Res., 2020)

Do Transformer Modifications Transfer Across Implementations and Applications? - 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 133; et al. (EMNLP (1), 2021)

GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding. - Dmitry Lepikhin; HyoukJoong Lee; Yuanzhong Xu; Dehao Chen; Orhan Firat; Yanping Huang; Maxim Krikun; Noam Shazeer; Zhifeng Chen (ICLR, 2021)

Searching for Efficient Transformers for Language Modeling. - David R. So; Wojciech Manke; Hanxiao Liu; Zihang Dai; Noam Shazeer; Quoc V. Le (NeurIPS, 2021)

GSPMD: General and Scalable Parallelization for ML Computation Graphs. - 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; et al. (CoRR, 2021)

Primer: Searching for Efficient Transformers for Language Modeling. - David R. So; Wojciech Manke; Hanxiao Liu; Zihang Dai; Noam Shazeer; Quoc V. Le (CoRR, 2021)

LaMDA: Language Models for Dialog Applications. - 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; et al. (CoRR, 2022)

Designing Effective Sparse Expert Models. - Barret Zoph; Irwan Bello; Sameer Kumar; Nan Du 002; Yanping Huang; Jeff Dean; Noam Shazeer; William Fedus (CoRR, 2022)

Scaling Up Models and Data with t5x and seqio. - 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; et al. (CoRR, 2022)

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity. - William Fedus; Barret Zoph; Noam Shazeer (J. Mach. Learn. Res., 2022)

PaLM: Scaling Language Modeling with Pathways. - Aakanksha Chowdhery; Sharan Narang; Jacob Devlin; Maarten Bosma; Gaurav Mishra; Adam Roberts; Paul Barham 001; Hyung Won Chung; Charles Sutton; Sebastian Gehrmann; Parker Schuh; Kensen Shi; et al. (J. Mach. Learn. Res., 2023)

Scaling Up Models and Data with t5x and seqio. - 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; et al. (J. Mach. Learn. Res., 2023)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)