Explicit Enumeration of Triangulations with Multiple Boundaries. - Maxim Krikun (Electron. J. Comb., 2007)

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation. - Yonghui Wu; Mike Schuster; Zhifeng Chen; Quoc V. Le; Mohammad Norouzi 002; Wolfgang Macherey; Maxim Krikun; Yuan Cao 007; Qin Gao; Klaus Macherey; Jeff Klingner; Apurva Shah; et al. (CoRR, 2016)

Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation. - Melvin Johnson; Mike Schuster; Quoc V. Le; Maxim Krikun; Yonghui Wu; Zhifeng Chen; Nikhil Thorat; Fernanda B. Viégas; Martin Wattenberg; Greg Corrado; Macduff Hughes; Jeffrey Dean (Trans. Assoc. Comput. Linguistics, 2017)

Reinforcement Learning based Curriculum Optimization for Neural Machine Translation. - Gaurav Kumar; George F. Foster; Colin Cherry; Maxim Krikun (NAACL-HLT (1), 2019)

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling. - Jonathan Shen; Patrick Nguyen; Yonghui Wu; Zhifeng Chen; Mia Xu Chen; Ye Jia; Anjuli Kannan; Tara N. Sainath; Yuan Cao 007; Chung-Cheng Chiu; Yanzhang He; Jan Chorowski; et al. (CoRR, 2019)

Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges. - Naveen Arivazhagan; Ankur Bapna; Orhan Firat; Dmitry Lepikhin; Melvin Johnson; Maxim Krikun; Mia Xu Chen; Yuan Cao 007; George F. Foster; Colin Cherry; Wolfgang Macherey; Zhifeng Chen; et al. (CoRR, 2019)

Beyond Distillation: Task-level Mixture-of-Experts for Efficient Inference. - Sneha Kudugunta; Yanping Huang; Ankur Bapna; Maxim Krikun; Dmitry Lepikhin; Minh-Thang Luong; Orhan Firat (EMNLP (Findings), 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)

Subtitle Translation as Markup Translation. - Colin Cherry; Naveen Arivazhagan; Dirk Padfield; Maxim Krikun (Interspeech, 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)

Scaling Laws for Neural Machine Translation. - Behrooz Ghorbani; Orhan Firat; Markus Freitag; Ankur Bapna; Maxim Krikun; Xavier Garcia; Ciprian Chelba; Colin Cherry (ICLR, 2022)

GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. - Nan Du 002; Yanping Huang; Andrew M. Dai; Simon Tong; Dmitry Lepikhin; Yuanzhong Xu; Maxim Krikun; Yanqi Zhou; Adams Wei Yu; Orhan Firat; Barret Zoph; Liam Fedus; et al. (ICML, 2022)

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)

Data Scaling Laws in NMT: The Effect of Noise and Architecture. - Yamini Bansal; Behrooz Ghorbani; Ankush Garg; Biao Zhang 006; Maxim Krikun; Colin Cherry; Behnam Neyshabur; Orhan Firat (CoRR, 2022)

Building Machine Translation Systems for the Next Thousand Languages. - Ankur Bapna; Isaac Caswell; Julia Kreutzer; Orhan Firat; Daan van Esch; Aditya Siddhant; Mengmeng Niu; Pallavi Baljekar; Xavier Garcia; Wolfgang Macherey; Theresa Breiner; Vera Axelrod; et al. (CoRR, 2022)

The Unreasonable Effectiveness of Few-shot Learning for Machine Translation. - Xavier Garcia; Yamini Bansal; Colin Cherry; George F. Foster; Maxim Krikun; Melvin Johnson; Orhan Firat (ICML, 2023)

The unreasonable effectiveness of few-shot learning for machine translation. - Xavier Garcia; Yamini Bansal; Colin Cherry; George F. Foster; Maxim Krikun; Fangxiaoyu Feng; Melvin Johnson; Orhan Firat (CoRR, 2023)

Gemini: A Family of Highly Capable Multimodal Models. - Rohan Anil; Sebastian Borgeaud; Yonghui Wu; Jean-Baptiste Alayrac; Jiahui Yu; Radu Soricut; Johan Schalkwyk; Andrew M. Dai; Anja Hauth; Katie Millican; David Silver; Slav Petrov; et al. (CoRR, 2023)