Shazeer, Noam

Attention Is All You Need

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 120,404

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2019) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 10,929

PaLM: Scaling Language Modeling with Pathways

Chowdhery, A., Narang, S., Devlin, J., Bosma, M., Mishra, G., Roberts, A., Barham, P., Chung, H. W., Sutton, C., Gehrmann, S., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2,590

Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks

Bengio, S., Vinyals, O., Jaitly, N., & Shazeer, N. (2015) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1,621

Gemma 3 Technical Report

Gemma Team, Kamath, A., Ferret, J., Pathak, S., Vieillard, N., Merhej, R., Perrin, S., Matejovicova, T., Ramé, A., Rivière, M., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 1,156

Image transformer

Parmar, N., Vaswani, A., Uszkoreit, J., Kaiser, Ł., Shazeer, N., Ku, A., & Tran, D. (2018) · arXiv

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 1,085

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

Fedus, W., Zoph, B., & Shazeer, N. (2021) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 1,005

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Shazeer, N., Mirhoseini, A., Maziarz, K., Davis, A., Le, Q., Hinton, G., & Dean, J. (2017) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 933

LaMDA: Language Models for Dialog Applications

Thoppilan, R., De Freitas, D., Hall, J., Shazeer, N., Kulshreshtha, A., Cheng, H.-T., Jin, A., Bos, T., Baker, L., Du, Y., et al. (2022) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 778

How Much Knowledge Can You Pack into the Parameters of a Language Model?

Roberts, A., Raffel, C., & Shazeer, N. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingInformation Retrieval and Search Behavior

Cited by 638

GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Lepikhin, D., Lee, H., Xu, Y., Chen, D., Firat, O., Huang, Y., Krikun, M., Shazeer, N., & Chen, Z. (2020) · arXiv

Parallel Computing and Optimization TechniquesAdvanced Neural Network Applications

Cited by 412

GLU Variants Improve Transformer

Shazeer, N. (2020) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 303

One Model To Learn Them All

Kaiser, L., Gomez, A. N., Shazeer, N., Vaswani, A., Parmar, N., Jones, L., & Uszkoreit, J. (2017) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 253

Fast Transformer Decoding: One Write-Head is All You Need

Shazeer, N. (2019) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 101

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69