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Nathanael Schärli
Nathanael Schärli
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Cited by
Year
Large language models encode clinical knowledge
K Singhal, S Azizi, T Tu, SS Mahdavi, J Wei, HW Chung, N Scales, ...
Nature 620 (7972), 172-180, 2023
20522023
Least-to-most prompting enables complex reasoning in large language models
D Zhou, N Schärli, L Hou, J Wei, N Scales, X Wang, D Schuurmans, C Cui, ...
arXiv preprint arXiv:2205.10625, 2022
10982022
Challenging big-bench tasks and whether chain-of-thought can solve them
M Suzgun, N Scales, N Schärli, S Gehrmann, Y Tay, HW Chung, ...
arXiv preprint arXiv:2210.09261, 2022
5672022
Traits: Composable units of behaviour
N Schärli, S Ducasse, O Nierstrasz, AP Black
ECOOP 2003–Object-Oriented Programming: 17th European Conference, Darmstadt …, 2003
5652003
Teaching large language models to self-debug
X Chen, M Lin, N Schärli, D Zhou
arXiv preprint arXiv:2304.05128, 2023
4592023
Measuring compositional generalization: A comprehensive method on realistic data
D Keysers, N Schärli, N Scales, H Buisman, D Furrer, S Kashubin, ...
arXiv preprint arXiv:1912.09713, 2019
3822019
Traits: A mechanism for fine-grained reuse
S Ducasse, O Nierstrasz, N Schärli, R Wuyts, AP Black
ACM Transactions on Programming Languages and Systems (TOPLAS) 28 (2), 331-388, 2006
3442006
Large language models can be easily distracted by irrelevant context
F Shi, X Chen, K Misra, N Scales, D Dohan, EH Chi, N Schärli, D Zhou
International Conference on Machine Learning, 31210-31227, 2023
3312023
Compositional semantic parsing with large language models
A Drozdov, N Schärli, E Akyürek, N Scales, X Song, X Chen, O Bousquet, ...
The Eleventh International Conference on Learning Representations, 2022
1252022
Compositional generalization in semantic parsing: Pre-training vs. specialized architectures
D Furrer, M van Zee, N Scales, N Schärli
arXiv preprint arXiv:2007.08970, 2020
1142020
Applying traits to the Smalltalk collection classes
AP Black, N Schärli, S Ducasse
ACM SIGPLAN Notices 38 (11), 47-64, 2003
832003
H Chi, Denny Zhou, and Jason Wei. Challenging big-bench tasks and whether chain-of-thought can solve them
M Suzgun, N Scales, N Schärli, S Gehrmann, Y Tay, HW Chung, ...
arXiv preprint arXiv:2210.09261 8, 2022
622022
Flattening traits
O Nierstrasz, S Ducasse, N Schärli
Universität Bern, 2005
542005
Object-oriented encapsulation for dynamically typed languages
N Schärli, AP Black, S Ducasse
Proceedings of the 19th annual ACM SIGPLAN conference on Object-oriented …, 2004
462004
Composable encapsulation policies
N Schärli, S Ducasse, O Nierstrasz, R Wuyts
ECOOP 2004–Object-Oriented Programming: 18th European Conference, Oslo …, 2004
382004
Traits: Composing Classes from Behavioral Building Blocks
N Schärli
University of Bern, 2005
352005
Traits: Tools and methodology
AP Black, N Scharli
Proceedings. 26th International Conference on Software Engineering, 676-686, 2004
282004
Traits: The formal model
N Schärli, O Nierstrasz, S Ducasse, R Wuyts, A Black
Technical Report IAM-02-006, Institut für Informatik, Universität Bern …, 2002
242002
Computerized systems and methods for extracting and storing information regarding entities
C Semturs, L Vandevenne, D Sinopalnikov, A Lyashuk, S Steiger, ...
US Patent 10,198,491, 2019
232019
A browser for incremental programming
N Schärli, AP Black
Computer Languages, Systems & Structures 30 (1-2), 79-95, 2004
222004
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Articles 1–20