Traits: Composable Units of Behaviour. - Nathanael Schärli; Stéphane Ducasse; Oscar Nierstrasz; Andrew P. Black (ECOOP, 2003)

Applying traits to the smalltalk collection classes. - Andrew P. Black; Nathanael Schärli; Stéphane Ducasse (OOPSLA, 2003)

Composable Encapsulation Policies. - Nathanael Schärli; Stéphane Ducasse; Oscar Nierstrasz; Roel Wuyts (ECOOP, 2004)

Traits: Tools and Methodology. - Andrew P. Black; Nathanael Schärli (ICSE, 2004)

Object-oriented encapsulation for dynamically typed languages. - Nathanael Schärli; Andrew P. Black; Stéphane Ducasse (OOPSLA, 2004)

A browser for incremental programming. - Nathanael Schärli; Andrew P. Black (Comput. Lang. Syst. Struct., 2004)

Uniform and safe metaclass composition. - Stéphane Ducasse; Nathanael Schärli; Roel Wuyts (Comput. Lang. Syst. Struct., 2005)

Traits: Composing Classes from Behavioral Building Blocks. - Nathanael Schärli (2005)

Flattening Traits. - Oscar Nierstrasz; Stéphane Ducasse; Nathanael Schärli (J. Object Technol., 2006)

Traits: A mechanism for fine-grained reuse. - Stéphane Ducasse; Oscar Nierstrasz; Nathanael Schärli; Roel Wuyts; Andrew P. Black (ACM Trans. Program. Lang. Syst., 2006)

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 038; et al. (ICLR, 2020)

Compositional Generalization in Semantic Parsing: Pre-training vs. Specialized Architectures. - Daniel Furrer; Marc van Zee; Nathan Scales; Nathanael Schärli (CoRR, 2020)

*-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task. - Dmitry Tsarkov; Tibor Tihon; Nathan Scales; Nikola Momchev; Danila Sinopalnikov; Nathanael Schärli (AAAI, 2021)

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. - Denny Zhou; Nathanael Schärli; Le Hou; Jason Wei; Nathan Scales; Xuezhi Wang 002; Dale Schuurmans; Olivier Bousquet; Quoc Le 001; Ed H. Chi (CoRR, 2022)

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 (ACL (Findings), 2023)

Compositional Semantic Parsing with Large Language Models. - Andrew Drozdov; Nathanael Schärli; Ekin Akyürek; Nathan Scales; Xinying Song; Xinyun Chen; Olivier Bousquet; Denny Zhou (ICLR, 2023)

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. - Denny Zhou; Nathanael Schärli; Le Hou; Jason Wei; Nathan Scales; Xuezhi Wang 002; Dale Schuurmans; Claire Cui; Olivier Bousquet; Quoc V. Le; Ed H. Chi (ICLR, 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 (ICML, 2023)

Teaching Large Language Models to Self-Debug. - Xinyun Chen; Maxwell Lin; Nathanael Schärli; Denny Zhou (ICLR, 2024)