Nathan Scales

According to our database, Nathan Scales authored at least 10 papers between 2004 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Large Language Models Can Be Easily Distracted by Irrelevant Context.

Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed H. Chi, Nathanael Schärli, Denny Zhou

Proceedings of the International Conference on Machine Learning, 2023

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Compositional Semantic Parsing with Large Language Models.

Andrew Drozdov, Nathanael Schärli, Ekin Akyürek, Nathan Scales, Xinying Song, Xinyun Chen, Olivier Bousquet, Denny Zhou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed H. Chi, Denny Zhou, Jason Wei

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Large Language Models Encode Clinical Knowledge.

Karan Singhal, Shekoofeh Azizi, Tao Tu, S. Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Kumar Tanwani, Heather Cole-Lewis, Stephen Pfohl, Perry Payne, Martin Seneviratne, Paul Gamble, Chris Kelly, Nathaneal Schärli, Aakanksha Chowdhery, Philip Andrew Mansfield, Blaise Agüera y Arcas, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Katherine Chou, Juraj Gottweis, Nenad Tomasev, Yun Liu, Alvin Rajkomar, Joelle K. Barral, Christopher Semturs, Alan Karthikesalingam, Vivek Natarajan

CoRR, 2022

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, Ed H. Chi

CoRR, 2022

2021

*-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task.

Dmitry Tsarkov, Tibor Tihon, Nathan Scales, Nikola Momchev, Danila Sinopalnikov, Nathanael Schärli

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Compositional Generalization in Semantic Parsing: Pre-training vs. Specialized Architectures.

Daniel Furrer, Marc van Zee, Nathan Scales, Nathanael Schärli

CoRR, 2020

Measuring Compositional Generalization: A Comprehensive Method on Realistic Data.

Daniel Keysers, Nathanael Schärli, Nathan Scales, Hylke Buisman, Daniel Furrer, Sergii Kashubin, Nikola Momchev, Danila Sinopalnikov, Lukasz Stafiniak, Tibor Tihon, Dmitry Tsarkov, Xiao Wang, Marc van Zee, Olivier Bousquet

Proceedings of the 8th International Conference on Learning Representations, 2020

2004

Modelling Electroosmotic Flow in Porous Media for Microfluidic Applications.

Nathan Scales, Niall Tait

Proceedings of the 2004 International Conference on MEMS, 2004